Usability of Smart Home Systems

MSc Program Die approbierte Originalversion dieser Diplom-/ Masterarbeit ist in der Hauptbibliothek der Tech- nischen EngineeringUniversität Wien aufgestellt Management und zugänglich. http://www.ub.tuwien.ac.at

The approved original version of this diploma or master thesis is available at the main library of the Vienna University of Technology. http://www.ub.tuwien.ac.at/eng

A Master's Thesis submitted for the degree of “Master of Science”

supervised by Em.O.Univ.Prof. Dipl.-Ing. Dr.h.c.mult. Dr.techn. Peter Kopacek

Teofil Lavu

01128525

Vienna, 15.04.2019

Affidavit

I, TEOFIL LAVU, hereby declare

1. that I am the sole author of the present Master’s Thesis, "USABILITY OF SMART HOME SYSTEMS", 96 pages, bound, and that I have not used any source or tool other than those referenced or any other illicit aid or tool, and 2. that I have not prior to this date submitted the topic of this Master’s Thesis or parts of it in any form for assessment as an examination paper, either in Austria or abroad.

Vienna, 15.04.2019 ______Signature

Powered by TCPDF (www.tcpdf.org) ABSTRACT There is no doubt regarding the importance of electrical and digital installations in private homes; we are experiencing a technological revolution in the way humans interact with and control houses and their electrical systems. After more than 90 years, during which traditional technologies in the electrical domain for domestic use were standardized, smart technologies and artificial intelligence gained an important place in the private home sector. The industrial sector was the initial pioneer which implemented this concept, with the purpose of production automation. Motivated by the continuous decrease of semiconductor costs, the vision of home automation, which is later associated with the term “smart home” became realistic and affordable, at least in the well-developed countries. Even if at first sight home automation systems seem only to provide the control for lighting and some power sockets, in a broader sense, we are talking about a complex power distribution system aimed to interconnect, control and monitor all types of electric based systems that can be found in the domestic sector. These can be, just to name a few, power appliances, switches, telephones, data networks, television, home theater, distributed audio, security monitoring and energy management. As smart home technologies get more affordable usability factors will increase the weight in the acceptability decisions made by users and purchasers. In addition, the great diversity of choices, equipped with different options and features, will require more time for learning and accommodation, which can in turn greatly limit the usefulness of new applications. Consequently, this thesis aims to make a critical analysis on how usable home automation systems are, as a matter of fact, beyond the promises made by the market place and the public messages spread by vendors and enthusiastic individuals about this topic. The present work does not have to be interpreted as skeptical or pejorative regarding smart homes but rather, it strives to present an objective and realistic view on this topic. For this matter, the analysis will use the actual state of the art as reference, and it will be based on case studies I was personally involved with, present research studies, papers, statistics and accessible data released by companies and organizations involved in this area. Firstly, this thesis will present an overview of the most common smart home architectures and technologies available on the market place, aiming to define a common ground for further discussion. On this basis, the analysis will further focus on 6 different aspects: 1. Social relevance – How do such systems impact and blend in our social life? 2. Economy – What costs are involved, in both the short and long term? 3. Environmental contribution – Does it positively affect our environment? 4. Interoperability – How well can different systems and technologies be interconnected? 5. Open Source – What is the standpoint of the market regarding the openness of smart home technologies? 6. Security – How secure are such systems and what is their impact on privacy? These topics impact the usability of smart home systems and thus their prosperity, as they are all related to user centered topics. Further, the subject can also be divided in two categories; (1) non-technical, which would be the first three topics and (2) technical, those being the latter three topics. Based on this analysis, conclusions are drawn aiming to raise awareness, where needed, and to encourage further emphasis on topics where great potential for improvement is given.

CONTENTS Abbreviations ...... 4 1. Introduction ...... 5 1.1. Motivation ...... 5 1.2. Definitions – Aspects covered in present work ...... 6 1.3. What this thesis is not about ...... 8 2. State of the Art - Present Technologies and Future Outlook ...... 9 2.1. Facts and figures ...... 9 2.2. Own conducted survey ...... 11 2.3. What Smart Home Systems Can Do Today? ...... 12 a.) Levels of Smart-Home Implementation ...... 13 b.) Home Energy Management System...... 14 2.4. Expectation from the future ...... 15 3. Technology - Different Approaches ...... 17 3.1. Components and Devices ...... 17 3.2. Centralized Architecture of a Smart Home ...... 19 3.3. Decentralized Architecture of a Smart Home (Fieldbus) ...... 19 3.4. Network based Smart Homes (IoT & WSN) ...... 22 3.5. The Home Energy Management System HEMS ...... 24 3.6. Summary ...... 25 4. Social Impact and Relevant Targeted Groups...... 26 4.1. Impact on Human-Computer Interaction and Behavior ...... 26 4.2. Target Groups ...... 28 4.3. Smart Home as a Social Disruptive Technology: ...... 29 4.4. Conclusion ...... 30 5. Economy - Short- & Long-Term Costs ...... 31 5.1. Material & Investments Costs ...... 31 a.) Low Cost Systems ...... 31 b.) High Cost Systems ...... 32 5.2. Energy Cost ...... 32 a.) Reducing Energy Costs ...... 32 b.) Increasing Costs Through Consumption?...... 34 5.3. Maintenance Costs ...... 37 a.) Low Cost Systems ...... 38 b.) High Cost Systems ...... 39 c.) General Challenges ...... 39 5.4. Switching Costs ...... 40

5.5. Conclusion ...... 40 6. Environment – Direct & Indirect Impact Of Smart Home Systems ...... 41 6.1. Aimed energy savings through deploying of smart home systems ...... 41 6.2. Short comes and issues ...... 43 6.3. Conclusion ...... 45 7. Interoperability – Available Options For Crosslinking ...... 46 7.1. Common Standards ...... 46 a.) Wired ...... 47 b.) Wireless ...... 48 c.) Interoperability beyond the protocols ...... 48 7.2. Gateways ...... 49 7.3. IP-based approaches ...... 49 7.4. Conclusion ...... 50 8. Open Source – Industry Openness on Smart Home Systems ...... 51 8.1. Open source licenses ...... 51 8.2. Can Open Source Smart Homes be completely free? ...... 52 a.) Software ...... 52 b.) Hardware ...... 52 8.3. Challenges of Open Source Solutions ...... 53 8.4. Availability of open-sourced Smart Home Systems...... 53 8.5. Conclusion ...... 54 9. Security – Impact on Privacy and Home Security ...... 56 9.1. Security Challenges and Solutions ...... 56 9.2. Privacy ...... 59 9.3. Hardware & Software Hacking ...... 60 9.4. Social Hacking ...... 61 9.5. Internet of Toys and their Privacy ...... 62 9.6. Conclusion & Outlook ...... 63 10. Summary and Outlook ...... 65 References ...... 67 Statistics on Publications and General Interests ...... 77 A.1. Number - Scientific Publications from 2007 to 2018 by Web of Science ...... 77 A.2. General Interests Based on Trends of Search Engine Google ...... 79 Own conducted survey ...... 81 B.1. Defining Questions ...... 81 B.2. Interviewed Companies ...... 81 B.3. Interview artifacts ...... 82

ABBREVIATIONS

BCU Bus Coupling Unit CAGR Compound Annual Growth Rate CSP Cloud Solution Provider CLA Contributor's License Agreement DR Demand Request ETS Engineering Tool Software HAN Home Area Network HEMS Home Energy Management System HTTP Hypertext Transfer Protocol GPL General Public License IoT Internet of Things IoToys Internet of Toys ISP Internet service provider KNX/EIB Konnex/Europäischer Installations-Bus MIMO Multiple-Input and Multiple-Output M2M Machine to Machine NAHB National Association of Home Builders OS Open Source PLC Programmable Logic Controller RF Radio Frequency RFID Radio-Frequency Identification SH Smart Home TAM Technology Acceptance Model VPN Virtual Private Network WSN Wireless Sensor Networks

1. INTRODUCTION This chapter presents in the first part the motives and drivers which encouraged the writing and the research for this thesis. The second part defines the framework and lists the objectives of the present work while in the last part aspects which will not be addressed here are enumerated.

1.1. Motivation

In 2012 I was given the opportunity to volunteer at a nonprofit foundation to support with the administration and maintenance of a building which had been recently bought. Around the year 2008, during a complete renovation, the building in question, was redesigned to meet the industry standards at that time. The refurbishment included the implementation of an automation system, meant to improve the management, maintenance and energy costs of the building. In 2012, after the foundation had purchased the building, I was offered the chance to help and assist at the recommissioning and adaption of the building automation system to fit the new demands. This project helped me to gain the first practical insight of building automation. Later in 2016, I began to study the field of home automation, motivated by relatives and close friends who were planning to either build a new house or to renovate an existing house. Along the planning phase, the above-mentioned home owners brainstormed with me on the idea to deploy smart home (SH) systems in their houses. My task in the preliminary phase was to do a general research about the state of the art of such systems, to compare and to choose the best option for their use case, based on my best knowledge. My credentials at that time were based on some acquired knowledge about automation from my former high school time. The research was conducted via various tools: web analysis of different approaches and systems, professional reviews, consumer reports, statistics and even a trip to a construction fair. At the fair I used the opportunity to get in touch with manufacturers and distributors of home automation systems. By gathering different views, from different stakeholders, I was able to get an overview on this topic (at least the theoretical aspect). In the second phase I focused on planning and designing the smart home systems for the respective houses. Along with the home owners and the electrician, we developed an electricity plan which had to be followed on the construction site. My task in the third step was to finally acquire the different components for the previously designed systems and to install them. In the last step I got the opportunity to experience modern smart home systems first hand and I was able to draw my own conclusions regarding their strengths and flaws. Further, I was able to understand the challenges such systems involve, the perspective of the end user, as well as the aspects of the engineer. The latter has the responsibility to develop a seamless solution, which connects components with different functionalities that might have been designed by different manufactures. The aimed result is a smart home eco system which should fulfill the purpose it was deployed to fulfill in the first place. These highly practically oriented projects brought me to light interesting aspects and insight which were not obvious in the first place. Followed by two similar projects (which are still in development), these were the initial driving forces that lead me to an in-depth research regarding smart home systems. The main objective was the quest for other projects, surveys and case studies that were reporting findings like mine, to confirm that my experience was not an isolated case. Secondly, my research focused on discovering new perspectives and approaches, designed to answer the shortcomings and the issues of current smart home systems, such that were also recognized by other researchers. Among others, the works of (Davidoff et al., 2006, Leitner & Harper, 2015, Hargreaves et al., 2017, Darby, 2017, Gerossier et al., 2018) and (Gazzawe & Lock, 2019) treat smart home technology issues, similar to my presumptions. Although the academic findings are not fully congruent with all the aspects I faced in real life, I was able to find common ground within a multitude of academic studies and connect them with my experience to form a harmonized picture. During this work I will use my recent projects on smart home systems as the main case studies on which my conclusions will be based on, but at the same time, I will back up my findings with other statements from the literature found throughout my research. I believe, however that the following is important to be mentioned, right at the beginning of the paper: Even if one could argue that this thesis tries to shed a negative light on smart home systems, the aim of it is to

5 present a realistic and critical overview over the present smart home systems and their usability. This approach is decisive to identify for instance, why the penetration of SH solution did not happen as expected by others, as (Leitner & Harper, 2015) stated. According to an estimation pointed out by (Aschendorf, 2014), around 95% of the electricians refrain from offering smart systems, whereas only 2% of the remaining 5% are really able to implement complex and intelligent controlling appliances. He further states that already 19 years ago, it was postulated by manufacturers, associations and electrical installers that in the shortest time, classical electrical installation will be almost completely replaced by bus systems. However, this goal has not been achieved to this day, and even new buildings are still often equipped with just the conventional installations. One of the reasons why former forecasts were inaccurate may root in the fact that research and simulation results can greatly deviate from reality, as it was also concisely pointed out by (Darby, 2017): “There is a striking contrast between the many research papers that estimate potential benefits from smart appliances/systems on the basis of simulations or trials in carefully controlled laboratory conditions and the handful that report on measured performance and acceptability in real-life conditions.” This is certainly not the case with every case study, and it is not the only reason for the shortcomings and unfulfilled expectations regarding smart homes. That is why I decided to write this thesis, with the scope to draw a general image on this complex and versatile topic. The reason for its complexity lays in the fact that such technologies cannot be isolated from the physical world and our social life, in fact, they were explicitly designed to positively impact our world and its environment. Accordingly, we are talking about technical systems which must harmonically cooperate with our society while being able to comprehensibly react to an indefinite number of unpredictable factors. After all, the journey of smart home systems does not head toward a dead end and I am a strong believer that there is still great potential in this technology, which is able to enrich our world and contribute to a positive development of our society.

1.2. Definitions – Aspects covered in present work

Both terms, usability and smart homes, are vast words which can be differently interpreted and understood by the reader, based on his/her background experience and expectation. For this reason, this chapter defines and explains the usability aspects of smart home systems discussed in the present work. However, the subjects discussed here are not intended to propose better solutions or approaches, but to raise awareness about the current situation and to grant the reader an insight beyond the vision and expectation of the present market. Smart Home The basic definition chosen by (Jiang et al., 2004), which according to Google Scholar was often used by researchers (cited more than 300 times) is that a smart home is “a dwelling incorporating a communications network that connects the key electrical appliances and services, and allows them to be remotely controlled, monitored or accessed”. The term ‘remotely’ describes the possibility that control points within the building can be accessed both, from inside and from outside of it. In this context, a home must contain three components: internal network, intelligent control and home automation, whereas the network is the basic part of a smart home. The network can be implemented by means of wire, cable or wireless. Chapter 3 presents an overview and a classification of these technology approaches. Usability In the context of smart homes and technology, the paradigm of usability focuses on the user and his/her needs, which often may look too obvious to be mentioned. (Shackel, 2009) discusses such considerations made by users. For instance, if “they feel it is suitable and they would like to use it, and how much it will cost, both financially and in terms of the personal, social and organizational consequences” then they will consider the product as usable. Regarding this aspect, he presents the acceptability equation which puts usability in a relevant context (see Fig. 1). As SH technologies get more and more affordable, as stated in (Kastner, Neugschwandtner & Kögler, 2005) or in (Gazzawe & Lock, 2019), usability factors will increase the weight in the acceptability decisions made by users and purchasers.

Fig. 1: The paradigm of usability and related concepts (Shackel, 2009) Furthermore (Shin et al., 2018) mentions that there is a difference between the perceived usefulness the perceived ease of use. While the first one defines the user's ability to utilize the system to improve his/her performance, the second one is the degree to which the user can use the system without efforts. He further stresses the idea that these two factors have a major contribution in the decision making by the user, when deciding between different systems. On the other hand, as (Saito & Menga, 2015) mention, the big variety of choices, equipped with different options and features, will require more time for learning and accommodation, which in turn greatly limits the usefulness of new applications. Therefore, I have chosen to focus on six main topics that, in my opinion, impact the usability of smart home systems and thus their prosperity, as they are all related to user centered topics. The addressed subjects can be also divided in technical and non-technical categories as follows: Non-technical topics: 1. Social relevance – How do such systems impact and blend in our social life? 2. Economy – What costs are involved in both, the short and long term? 3. Environmental contribution – Does it positively affect our environment? Technical topics: 4. Interoperability – How well can different systems and technologies be interconnected? 5. Open Source – What is the standpoint of the market regarding the openness of smart home technologies? 6. Security – How secure are such systems and what is their impact on privacy? In a similar tone to the 6 topics suggested in this thesis, (Shin et al., 2018) extended the well-known technology acceptance model (TAM) by (Davis, 1989) and added two additional criteria – Privacy and Compatibility – in order to evaluate and identify the consumers of smart home systems more accurately, as shown in Fig. 2.

Fig. 2: Extended technology acceptance model (TAM) model (Shin et al., 2018) To define a common ground and to provide an overview on these topics, two chapters will follow whereas Chapter 2 elaborates on the state of the art functionality and Chapter 3 on the technology from a contemporary perspective. These build also the basis on which the six topics listed above will be discussed.

1.3. What this thesis is not about

Given that this is a very large domain, this thesis does not cover the following aspects as they would go beyond the scope and core of it. - Benchmarking and comparing of different systems against each other. - Decision making whether a technology or design is better that the other. - Proposing new systems and technologies - Forecasting the future of smart home systems or expressing concrete expectations about their development However, based on this research and finding, new ideas and approaches can be developed to further drive this technology.

2. STATE OF THE ART - PRESENT TECHNOLOGIES AND FUTURE OUTLOOK This chapter presents firstly statistics about actual trends in SH technologies. In the second part it introduces the reader in the set up and the first brief insights of a self-conducted survey. Third part discusses about some general features, functions and possible way to categorize the different components of it. Finally, the last part talks about future developments of these technologies and what are the hot topics in research at the moment.

2.1. Facts and figures

The current statistics suggests that the global smart home market value will hit $40 billion by 2020 and $53.45 Billion by end of 2022, as stated by (Zion Market Research, 2016). Further, household penetration is expected globally to grow up to 22,19% by 2023 from 5,27% in 2017 as shown in Fig. 3. This growth is projected because of the increasing demand for smart home systems around the world.

Fig. 3: Smart home Penetration between 2017 and 2023 (Statista, 2018) Consequently, the demand for smart products is growing. Currently, based on a case study done by (alarms.org, 2018) 63% want smart thermostats and smart alarms and locks, 56% want carbon monoxide sensors, 58% want smart lighting. Several guesses have been made on the growth rate of smart home market in the next few years. One of the motives for the demand increase is, as expected (and promised by the manufacturers) that it makes one’s daily lives more convenient, easy, and reduce the total operational and maintenance cost. According to a study conducted by the same company mentioned above, in the United States, the statistics showed that more than 57% of the Americans acknowledged that smart appliances saves them about 30 minutes daily which totals 182.5 hours annually. In another study, analysts have estimated that by 2020, more than 500 million smart home appliances will be shipped worldwide, approximately 150 million cars will have connection to the internet, an estimated revenue of $300 billion will be generated by internet of things, and smart home automation market will be valued at $21 billion (Kimberly, 2017). Further, because IoT and smart homes are nowadays terms with strong relevance to each other (and often mixed together), the next findings are also meaningful to be addressed: Based on a study carried out by (IHS, 2015), the number of IoT devices worldwide in contrast to 2019 (26.66 billion) will be almost tripled and it will reach 75.44 billion by 2025. Fig. 4 presents these forecasts in a bar graph.

Fig. 4: IoT connected devices installed base worldwide from 2015 to 2025 (in billions) (IHS, 2015) When looking at the market share numbers, the trend is confirming the same facts: a continuous growing of smart home appliances. As seen in Fig. 5, a growth rate of 13.2% is expected between 2017 and 2023 with a market value of $44.7 billion by 2023.

Fig. 5: Forecast market size of the global smart home market from 2017 to 2023 (in million dollars) (Statista, 2018) Another essential aspect that is analyzed in this context, is the number of publications in the last years. Not surprising at all, the trend regarding scientific works, is similar to the market’s one. The trend analysis of publications was done on the analytics web platform webofknowledge.com. The first search was done on the topic with the Key words “smart home”. It revealed that in the last six years (2013 to 2018) more than 7000 publications were written, in contrast to the six years before (2007 to 2012), where only about 2000 scientific papers have been published. So, the number of publications has increased more than by triple. The same search was done on the topics or the title including “IoT”, “IoT AND Smart Homes” and “IoT OR Smart Homes”. The results exposed similar findings and trends. For the exact results, the graphics to this analysis can be found in 0, A.1 ‘Number - Scientific Publications from 2007 to 2018 by Web of Science’. Last but not least, the general interest on these topics can also be analyzed by looking to the Trends search engines like Google publishes. The results show undoubtfully an increase of awareness for these subjects among people across the planet. For more details on these trends and comparison, see 0, A.2 ‘General Interests Based on Trends of Search Engine Google’.

2.2. Own conducted survey

I got the opportunity at the 18th Edition of the building trade fair held in Vienna between 14th and 17th February 2019 to conduct some interviews with firms and manufacturers from the electrical installation industry. In doing so, I was able to get a first-hand insight about what the market can currently offer. This is a look beyond the concepts in theory and the research, which otherwise is helpful and required, but not enough. The companies interviewed can be divided in two groups, Production and Sales, whereas some companies are found in both sectors. The following table enumerates the interviewed companies. In second row type of company is mentioned. Table 1. Interviewed Companies Company Type

Abb AG Production & Sales ABUS Austria GmbH Production & Sales Albrecht Jung GmbH & Co KG Production ATsmarthome360 GmbH Sales Busch-Jaeger Elektro GmbH Production Capro GmbH Sales EURO UNITECH Elektrotechnik GmbH Sales evon GmbH Production & Sales Gira Giersiepen GmbH & Co KG Production & Sales S. Siedle & Söhne, Telefon u. Telegrafenwerke OHG Production & Sales smart:ex Haustechnik & Elektrotechnik / Siblik Smarthome Sales SpeedTech Save & Cool GmbH Sales VELUX Österreich GmbH Production To avoid any subjective judging towards a specific firm or brand, and to disable pointing with the finger to any of the interviewed ones, the answers are anonymized. Thus, they are not directly linked to the interviewed firm itself. The aim of this survey is to get a general idea of the actual market status and to understand the direction it heads to. Following list enumerates findings that could be made from these interviews. The exact notes taken during the interview and the questions asked can be found in Appendix B. Technology & Features: All companies offer almost the same features. Some of the common features present at all producers: - Control for Lighting, Blinds, Heating, Secure Access, universal digital and analog inputs and outputs - Local and Remote Control - Almost same security Standards - Mobile device support through Web or proprietary App (Smartphones, Tablets PC) - Most companies work with fieldbus Loxone, KNX or Z-Wave as communication protocol Open Source: Commercial smart home Products offer almost no opensource software/platform. The only approach is given at the companies which uses KNX as fieldbus, thanks to its given open standard. Based to some reports, this may be related to competition concerns. Security: For remote access, almost everyone is preferring the VPN or clouds, solution, whereas the first one is more often the case, due to safety consideration. Other safety measures are not taken or are defined 11 by the standard implementations in use. According to some companies, “there is no need for further actions”. Troubleshooting & Maintenance: Most companies offer troubleshooting and maintenance at working hours and on working days. Just one seller is offering 24h/7 days troubleshooting services. The maintenance is done locally or with remote hands, depending of the company and the user requests. Interoperability: This is seen as an extra feature by any company. The only possible way is to whether buy specific gateway from third parties (which is not guaranteed to be available for any use case), or to use available potential-free contacts (available depending on device and function) which would enable one- way information transmission through open/closed contact positions.

2.3. What Smart Home Systems Can Do Today?

We are currently witnessing an exponential growth in smart home solutions, and the market is booming in offering different approaches, but with the same aim, and same complexity. By this, the effective result of such systems is most of the cases similar with every solution. Even if the mainstream talks about solutions that promise to be ‘innovative’, this is only partly true; Such systems and concepts are not new and they began to gain a significant popularity in the 1990s (Gergely, 2018) while the idea of home automation itself came into being almost four decades ago, initiated by the National Research Center of the National Association of Home Builders (NAHB) (Hamed, 2012). The main improvement that home automation systems achieved in the last decade, were thanks to the technical progress of computational and microprocessor units, which facilitates higher computing performance, while keeping or even reducing the size of such components (Garbett, 2014). (Gazzawe & Lock, 2019) have argued that the advancement of smart home technology has been attributed to four primary factors. They include: i) Micro-controllers high processing power ii) Miniaturization of semi-conductors has progressively increased iii) Advancement in wireless network technology iv) It is now possible to integrate signal conditioning in small sensor nodes (Hsu et al., 2017) These are the key factors that have contributed immensely to deploying smart home systems to various households at a cheaper cost further claims Gazzawe and Lock. In addition to the four factors, emergence of Home Area Network (HAN), which is a network technology specifically designed for smart home systems has made it possible to offer two-way communication between the different smart home components, distribute energy storage and generation, and metering of infrastructure. HAN technology also accommodates the common wireless and wired communication protocols such as Bluetooth, PLC, WiFi, 12C, RS485, Homeplug, RFID, SPI, and GPRS. Today, it is possible to control the various smart home devices from one main control panel making one’s household feel better, run smoother, and save energy. It is important for consumers when identifying a home automation system to consider the ones that will meet their current and future needs. Further, there are professionals who can design custom made home automation systems that will be able to meet all your needs because your desired features will be incorporated to make interaction with the system easier and more enjoyable. Such an example was studied and documented by (Gergely, 2018). Generally speaking, functions of smart homes can be summarized in these 4 categories, as (Aschendorf, 2014) also suggests in his book: • Comfort: there are a variety of such examples and even the comprehensive enumeration proposed by Aschendorf is not complete, as he admits. But in principle this category covers all possible control of loads and devices within a household. • Security: This category includes the evaluation of binary and analog sensors, by which different positions, states and conditions of the physical world of a home can be determined. Thus, different safety related assumptions can be made. • Energy management: These functions are discussed in more detail in chapter 3.5.

• Multimedia: All devices which have a human-computer interface like monitors, touch panels, mobile devices, or other input and output devices are covered here. Their purpose is to interact with humans by (1) taking different inputs from them and (2) Providing information in different formats that can be precepted by all six human senses. Form a feature perspective, (Sam, 2017) presents 4 different topic which describes the main subjects regarding a smart home: • Interoperability - smart home systems has made it possible to tie together diverse home electronic devices to work as a unified system. However, integrating these devices together can be complex or simple depending on the automation system openness, thus open systems makes it easier to allow thermostats, lights, security devices, and other home electronic devices to communicate with each other. Manufacturers and developers of home automation systems have formed a partnership to ensure interoperability of many electronic devices. • Remote access - such systems has made it possible for home owners to control and monitor their smart home appliances form anywhere. This is a very important feature because many at times plans change when you are away from home and you may want to turn on/off security lights, warm food, among other functions. Additionally, in case you experience some problems with your smart home system, it will allow your service provider to tweak the systems without having to physically come to the house making it cheaper and more convenient. • Expandability - the current smart home systems supports addition of new gadgets into the systems without having to alter the current setup. Technology will continue to advance and five years from now more advanced gadgets will be available and one may need to upgrade their home devices and add new rooms to the automation system. This functionality is very essential to facilitate vertical expansion to incorporate new components and horizontally to support more rooms. • Energy Management - this feature is separately addressed in section 3.5. a.) Levels of Smart Home Implementation (Aldrich, 2003) suggests a means that can be used to categorize the various smart home solutions based on their complexity and availability nowadays. At the same time, this enumeration is relevant because it also presents the evolution of complexity of smart homes from its beginnings. This project will adopt the same classification approach to further explain about the various range of tools and options of such systems. 1. homes with intelligent components: these are homes with single and stand-alone gadgets and appliances that operate intelligently. 2. homes with communicating and intelligent appliances: this includes homes with gadgets and appliances which can operate in an intelligent manner but can also communicate and exchange information with other appliances to enhance efficiency and increase functionality. 3. connected homes: these are homes with both external and internal networks to facilitate remote and interactive systems control and ability to access the appliances both at home and away from home. 4. learning homes: systems have the ability to record the daily activities of the home users and use them accordingly to predict and anticipate consumer’s needs. 5. the attentive homes: the location and activity of the various appliances, gadgets, and people are registered regularly to control technology regarding the expectations of the consumer’s needs. Based on these 5 complexity levels of smart home solutions and with the research and the present case studies in mind, I conclude with confidence that the state of the art of smart home technologies reached the fourth level, namely, the improvement of learning homes. Although these concepts are already present on the market, actual research is trying to bring learning homes at a robust state by using artificial intelligence (AI) (see for instance (Shareef et al., 2018) for such implementations), but this is not so easy, as I will present in the following chapters. However, it is important for manufacturers to pay attention to these different levels of smart home implementation and ensure that consumers get what they need and not what the manufacturers are offering (Yang, Lee & Lee, 2018). Every consumer has different needs and expectations of a smart home automation system. As also argued by Yang & Lee, they often get

13 features they don’t ask for and miss others which they would need. It is not uncommon that these demands aim at simpler solutions regarding only complexity levels between one and three. Finally, some aspects and challenges regarding the level 4 and 5 mentioned above, are comprehensively addressed in a review by (Ms. Falguni Jindal, 2018). The following paragraph briefly summarizes the main findings relevant to this work. Among other things, Jindal talks about the possibilities that result from the emergence of AI Algorithms; The IoT scope is wide and with the integration of artificial AI it will become more widespread. AI utilizes sensors, machine learning, and pre-collected data to preserve human preferences and response, that is, its main selling point is adaptability. However, the fusion between IoT and AI brings about the issue of data integrity. Data can be compromised by either the device manufacturers or intruders. Anonymity is then another issue arising with integration of IoT with Blockchain. Anonymity is crucial in preserving the data owner’s identity. These technologies should not disclose the identity of a data owner in public networks. Also, IoT application professionals are few. Just like any other technology field, the enhancement of IoT domain depends completely on the domain experts available. There are limited IoT experts available today and this is the reason why more than 68% of companies are struggling to get these experts. b.) Home Energy Management System Home energy management systems (HEMS) have been considered as one way to control and understand electricity consumption, emissions, and costs. In the research conducted for this work, I conclude that most of the publications mentions in some way or the other the importance meaning of HEMS (see for instance, (Jaouhari et al., 2019, Khan et al., 2019, Yu et al., 2019) or (Nilsson et al., 2018)). Some of the current market examples of HEMS products include CarbonTrack, Solar Analytics, smartfox and BlueSky Energy whereas the latter two are relevant to the European market. According to (Potter, 2017), HEMS have four key factors of home energy that they can be involved in. Some HEMS have incorporated all the four aspects while other have only incorporated one or two. These aspects include electricity, solar PV, solar thermal, and battery storage. There are several factors that should be looked into while assessing a home energy management system. CarbonTrack is one of the popular providers of HEMS and is known to be leading both in terms of technological advancements and price. There are several features that HEMS should have but for the purpose this work, it will sufficient to mention five of them. i) A reliable HEMS should allow consumers to control and monitor their home energy usage. ii) Secondly, it should allow the users to control their home appliances remotely. For instance, users should be able to turn off lights when not in use while away from home. iii) Thirdly, HEMS should provide insights the users that will facilitate them to save and use energy more efficiently. iv) It should identify and record user’s habits and work automatically around them. v) It should have the ability to integrate with battery storage and solar power seamlessly. According to (Shareef et al., 2018) many researchers have shown interest in residential demand response (DR) program in the recent years. DR tool is incorporated into the HEMS to curtail and shift demand to enhance home energy usage. DR tool usually creates a schedule to ensure optimal energy consumption by taking into consideration a number of factors like energy cost, load profiles, environmental concerns, and consumer comfort. It has now become possible to perform load control using HEMS with DR-enable appliances because of deployments of smart meters. Technology advancement has led to introduction of intelligent HEMS for smart homes to provide strategies for saving energy and reducing emission of greenhouse gases. Smart home technologies have facilitated integration of intelligent HEMS to the different home functions like automatic control, using smart meter to connect to the utility, and reducing energy consumption. However, based on the market analysis and the case studies I am involved in, one has to admit that at least for the European market, there are not many marketable HEMS solutions, and this may be related to the fact that the present electricity infrastructure in most European countries is not equipped with smart meter, which is a key factor in successfully deploying efficient HEMS. By 2014, Sweden was the country which had the highest smart meter coverage which was higher than 90% (Nilsson et al., 2018), however this is not the case for most of the European

14 countries. At the moment, another reason for the low presence of the market of such systems may lay in the fact that there are currently no available Demand Request (DR) principles for electricity pricing plans, thus some features may remain not deployable at the moment.

2.4. Expectation from the future

The changes that have been experienced in home automation technology during this time are acute making the future expectations more technophile. Many devices and smart home appliances are being introduced in the market every day. Research reports that have been published recently indicate that the global smart homes and buildings are anticipated to grow significantly at a CAGR of more than 29% between 2017 and 2022 (Rodriguez-Diaz et al., 2016). The main drivers to these chances are attributed to climate changes and the need for reduction in carbon emissions and sustainability, the consumers’ wanting to control all the appliances in their homes, and technology inventions (GhaffarianHoseini et al., 2013). However, (Gubbi et al., 2013) uses the Gartner hype cycle to argue that expectations from smart homes and especially IoT had have an peak in last years and then they dropped radically as first issues and challenges, beyond the promises and dreams of enthusiasts, began to come to light. Nonetheless, as one can easily recognize in Fig. 6 , we are currently in the phase called Plateau of Productivity, where mainstream adoption starts to take off and slowly standards and more company began to deliver more stable and efficient solutions.

Fig. 6: Future expectation of smart home systems (Gubbi et al., 2013) From a more technological point of view (Gubbi et al., 2013) also presents a roadmap of technology, in which IoT will play a central role for different application domains. But the vision of the future is that smart IoT devices will emerge on the market which will have Plug-and-Play capability. By this means, no specific customization and troublesome integration will be needed, for every single device in particular. This roadmap is pictured in Fig. 7 , where past present and future technologies are grouped by application domains with regard of their timeline. In the same fashion, scientists around the globe are continuously looking for new approaches and technologies which will improve the principal concept of smart homes. There are a variety of new approaches regarding this, but I will focus int the next subpoints on three concepts, which I think, will have a big impact in this domain, as soon as they will be implemented and will emerge on the market.

Fig. 7: Roadmap of Technologies with the context IoT (Gubbi et al., 2013) The Future smart DC home Climate change is evident and real, and this has been caused by human activities. The international communities are considering adoption of renewable energy and shift away from fossil fuels. Many countries are still depending on oil, gas, and coal as their primary source of energy and this has greatly affected the climate around the world because of the excess emission of carbon gas causing global warming. As such, it is expected that the future smart DC home should be able to consider this fact and ensure that there is no emission or if it is there it should be minimal. The future DC smart homes should also support what we now call “the green energy” and provide insights on how to better use it efficiently. It is expected that the smart DC will be able to integrate microgrid because it simplifies integration of energy storage systems (ESSs) and renewable energy source (RESs) at consumption level with the intention to increases efficiency, reliability, and power quality (Rodriguez-Diaz et al., 2016). Moreover, the increasing use and presence of smart appliances and gadgets in homes reveals a promising future for smart DC homes, where smart devices integrate and work with residential power systems to attain a more sustainable, smarter, and cleaner energy systems (Riccobono et al., 2016). Smart Building materials With advances in technology, it will not come as a shock when walls will have the ability to paint themselves, measure light levels, and temperature. (Gubbi et al., 2013) concludes that it is expected that the future buildings will be able to identify the tenants or owners, monitor their actions, and take necessary actions to ensure their safety and comfort. This will also be supported by the current emerges on the market where we have high performance concrete, aerated concrete, floating concrete, light transmitting concrete, and pervious concrete. This has been made possible by the advances in technology (Mehrabian et al., 2013). By this approach, the SH implementation at level 5, as presented in section 2.3.a.), moves closer to reality. More efficient low powered PLC With the growing trend of IoT, where every endpoint can be seen like a mini computer, PLC devices are demanded and there is a high interest to improving this technology by making use of the MIMO concept. This allows higher processing rates at lower power consumption. Furthermore, because of the increasing number of wirelessly deployed devices, these PLC are getting improved toward the CENELEC EMC standard EN50561-1 for in-home PLCs. (Saito & Menga, 2015) addresses this topic and states that these “features have just been recently developed or are currently under development by chip manufacturers, so that products offering them will access the market soon”. 16

3. TECHNOLOGY - DIFFERENT APPROACHES As the subject is vast, so the technologies and the are available with a big variety. This chapter firstly presents a brief overview over the components of smart homes followed by the three most common smart home architectures. These three approaches can however be combined to offer different efficiencies for specific needs. In the final part a specific application for smart homes will be presented, namely the Home Energy Management System (HEMS).

3.1. Components and Devices

Smart homes are composed of several components and the literature uses different ways to group them in categories. For instance, (Hamernik et al., 2012) divides devices by their functionalities and scope of application, as comprehensively shown in Fig. 8. At the same time, some devices will belong to multiple categories or they will accomplish tasks for different function. For instance, a motion sensor can simultaneously deliver motion information for both lighting and safety functions. However, the configuration in Fig. 8 only show a standard sample of what a smart home system can offer. This can be easily extended to new functions as they emerge on the market. Furthermore, a smart home must not contain all function covered in this graphic, but it will be tailored to the needs of the user.

Fig. 8: Standard Functions of a smart home (Hamernik et al., 2012) 17

This thesis suggests however a more general approach. The categories in this case define the technical ability and their purpose(s) in the system. Thus, it can be said that this listing has a more technical approach than the previous variant mentioned above. The following list presents these categories along with a short description and a few specific examples: 1. Input Devices This category covers any device which facilitate any type of information input. Analog to the human sensory organs, this category can also be seen as the sensing domain of a smart home system. Such devices can be tasters, voice recognition, touch screens or any other type of sensor. Sensors can basically be divided in three categories: a) Binary/Digital Sensors A sensor commonly used in smart homes is the dual sensor, which simply detects the state of an object or movement using a single number "1" or "0". Various types of binary sensors have been used in smart homes, including motion detectors, pressure sensors and communication switches. The advantages of simple binary sensors result in low cost, easy installation and a low level of confidentiality. However, these sensors only provide information at an abstract level and are therefore limited to infer activities. b) Analog Sensors All activities that cannot be conducted by only two states can by assessed and tracked by analog sensors. Measuring the temperature, humidity, light intensity, pressure intensity, distance or color are just a few applications where analog sensors find their purpose. However, to digitalize such information and to make it available for different applications is a more complex task in comparison to the analog sensors, because one has to take care about multiple aspects like resolution, accuracy (including nonlinearity), jitter, or sampling rate digit. c) Sensor combinations systems All devices that need more sensors coupled together to deliver a relevant info can be seen as sensor combinations system. Such examples are for instance cameras or touch screens, as they use for every pixel a photo-sensor (for cameras) or a pressure/capacitive sensor (for touch screens). 2. Actuators In order to control loads or to act in the physical world, smart homes systems use devices named actuators. These can be relays, contactors or motors. By this, lights, blinds or doors, to mention a few, can be controlled and adjusted. Actuators are in general commanded by controlling units. 3. Processing and controlling units The place where signals are received, interpreted, processed or transformed to actions is called the processor or controlling unit. Some systems are ruled by one or multiple such units. Some examples are, computers, digital boards, gateways, databases or home servers. 4. Connection means For the signal to travel between Sensors, processing units and actors a medium and a channel is needed. Some examples are, power lines, network cables, fieldbus cables or wireless signals. In order to communicate and understand the signal, the same communication protocol is used by every participant, receivers and senders. These aspects have to be agreed by both sides, and each communication peer has to be capable to use the regarded protocol. 5. Output devices Every consumer that transmits an information to the physical world with the purpose to be received, understood and used by humans (that in fact, are the final beneficiaries of the smart home system) are output devices. This can be as simple as a light and it can range to a complex device like a 3D hologram. Other examples are, displays, projectors, speakers, video and audio devices. Based on this listing, the next sections regarding possible smart home architectures will be discussed.

3.2. Centralized Architecture of a Smart Home

In a centralize smart home, the heart unit of the complete automation system is a central processor unit. There are mainly two cases in which more than one central unit will be deployed: • to achieve a redundancy or load balancing or • because due to the design of the building there are more than one electrical cabinet. This can be the case of a multi-storey house, for instance. Further, to the central unit, all other components are connected by wires or through wireless access points. There are basically to types of components: • Internal: These are modules mostly located next to the central unit and can be extended easily. These components can be input/output interfaces or actuators. • External: This includes all devices that are strategically located at specific locations in the building. Based on the listing in 3.1 Components and Devices, these are either input or output devices. In Fig. 9 (Wisser, 2018) explains this architecture by a sample schematic:

Fig. 9: Architecture of a centralized smart home System (Wisser, 2018) This architecture approach is the more classical approach. In my survey at the building fair (see 2.2), only one manufacturer still uses this approach. However, this strategy has also advantage, which justify its presence on the market. In following advantages and disadvantages are listed: Advantages: 1) Reduced number of digital units, thus, reduced complexity of the system; 2) Single point of truth, so systems are easy to debug and troubleshoot; 3) Reduced risk of security sensitive touch points (in comparison to the other technologies); 4) Possibility to deploy low cost devices, for example by using universal contactors and sensors; Difficulties: 1) Complicated and costly wiring system; 2) Not flexible and versatile. Hard to extend, modify or interconnect with other systems; 3) Most solutions are proprietary (so, not open source), reason why it is not friendly for customizations directly by the user; 4) Single point of failure: If the central unit fails, (In case of breakdown) complete house system is paralyzed.

3.3. Decentralized Architecture of a Smart Home (Fieldbus)

Decentralized systems are currently the proven frameworks and are currently mostly provided by manufacturers on the market. In contrast to de centralized architecture, this approach is distributed and

19 has not only one central place for all processing, but rather more smaller units which can process a reduced number of signals and commands. In fact, almost every component of the system has a digital processing unit (also called as control node), which has some reduced functionality (intelligence) integrated. Because of this aspect, this approach is also known as a collaborative control architecture. A simplified sample architecture is presented Fig. 10.

Fig. 10: Architecture of a decentralized fieldbus system (Angulo & Tellez, 2004) For enabling the communication, a fieldbus is deployed. This is defined by a specific standardized protocol. A fieldbus can be seen as an ethernet network, but with slightly simplified layers. The principle of such a bus is shown in Fig. 11. The communication channels can be achieved either through wires or wirelessly.

Fig. 11: Fieldbus communication principle (Saito & Menga, 2015) As already mentioned, for the system to be operational, there is no central unit needed, however in some situations, there is a special unit, for instance a server (often called Home Server) that has an overview and it can take over more complex tasks. Following lists some advantages and disadvantages of such architectures. Advantages: 1) No single point of failure: if one device fails, the rest of the systems remains operable. 2) Network grouping is flexible, e.g. to isolate some part of the network because of security reasons. 3) System can easily be extended with further input and output devices Difficulties: 1) System may be more expensive, as every device is equipped with microprocessors. 2) Security tends to be a bigger issue in this case, because: a. there are more entry points into the bus system (every fieldbus connected device which is located at different points in the house) and b. communication over these simplified protocols are often not secured enough (e.g. because of plain text data transmission). 3) Not easy to implement in old building while renovation Two of the implementations of this architecture, that are well known on the European market are EIB/KNX and Loxone. Next section will briefly describe EIB/KNX based systems, because this technology is also partly used in the case studies reported in this thesis.

EIB/KNX Based Systems

EIB/KNX based Systems is an abbreviation of the European Bus Technologies standard which is a form of decentralized open system technology for managing and controlling electrical devices within a specific facility. The founders of the initiative were well known companies including GIRA, Merten, Siemens, Berker and Jung. The project started back in the early 90s with the vision to introduce a common standard on the market. It is mostly used for data exchange between different objects for the purpose of controlling, supervising, reporting or performing basic functions in the electrical building installation (Aschendorf, 2014). The technology is specified over various physical media such as powerline and twisted pair. For this technology, it is provided by the manufacturers with ready-made applications which should match with specific hardware. Such applications have the behavior in the sense that they can be customized by the project engineer by modifying the application parameters to suit the needs of the user. The software for programming or parametrization is called ETS (Engineering Tool Software, formal called EIB Tool Software) and is running on Windows based platforms. In this case, the final configuration is then downloaded through the Bus Coupling Units (BCU) into the device. Since each participant has its own microcontroller and memory, no central control unit is required in principle, thus we are talking about a decentralized system. Linux operating systems are relevant in the developing of new devices, because of the imbedding of kernel level drivers for BCU which are implemented for accessing the services over the network (Kastner, Neugschwandtner, Soucek & Newman, 2005). The data transmission and bus voltage supply of the KNX / EIB is via two wires, while the data transfer rate is at 9,600 bit/s and the standard voltage is about 28V DC. The function of the member units is however guaranteed within a tolerance of the bus voltage of 21V to 30V. The maximum power of each device is limited to 200mW. The addressing of the devices within the fieldbus is done by a three-level identification in the from [--].[--].[---]: (1) area level (2) line level and (3) unit level. There can be 15 areas, 15 lines and 64 participants. By deploying line amplifiers, up to 256 units can be interconnected (Aschendorf, 2014). Thus, up to 57.600 (15 × 15 × 256) bus participants can be addressed in a KNX world, consequently the maximum address is 15.15.255. Fig. 12 presents the possible architecture of the KNX technology from the perspective of addressing.

BK: Area coupler LK: Line coupler TLN: Participant/Unit SV: Power Supply Fig. 12: Structure of the three levels of addressing in the KNX world (Aschendorf, 2014)

The work flow of developing the EIB/ KNX is divided into 3 key steps, which include: Development whereby the software developer writes BCU application program based on a specific hardware configuration. The developer documents its behavior and clearly defines the available parameters that influence its operations. The second step is project planning whereby the project engineer chooses the best EIB/ KNX devices to fulfil the requirements of a step. The last step is installation parametrizing and download whereby the BCU applications are combined with the necessary application modules and then installed to the destination.

3.4. Network based Smart Homes (IoT & WSN)

A decentralized system with a similar architecture like the one described in section 3.3 can also be achieved by replacing fieldbus standards mostly with LAN protocols from the IEEE 802 family, and the fieldbus wires with Ethernet cables (IEEE 802.3) or wireless signals (e.g. IEEE 802.11). By doing so, the smart home system turns into an IP network. Typically, communication systems are further grouped by networks on every floor, and sensors and actuators are connected at the room level (Kastner, Neugschwandtner, Soucek & Newman, 2005). Similar to the listing presented in section 3.1, (Han & Lim, 2010) states that there are 3 primary components that make up this technology. These include the physical component which comprises of electronic devices, sensors and actuators. The second component is the control system which comprises of experts/ intelligence system and finally the communication system which link physical components with the control components. The control-system can be accessed from home-exterior through the external home network just like mobile networks or internet. In a smart home system, the physical system senses the environment and pass the information to the control system through home network and sub networks. The home control system does the inferencing by making a decision and later it passes this information to the actuators through home network. For instance, a gas sensor may detect the leakage of the gas in smart home and then passes this information to the home control system, via a wireless network. The control system makes then the decision to switch off the gas and passes this decision to the actuator, which will actually switch off the gas. As seen in this example, control systems obtain information from various sensors and then categorize it based on the different types of activities. Several machine models make use of artificial intelligence to recognize the activity in a smart home application. The communication system is mainly used to share information between physical system and control system and as mentioned in the beginning, it can use wired or wireless technologies or a combination of them. A specific use case is when most of the devices are wirelessly connected. In this case we talk about Wireless Sensor Networks (WSN). Technologies listed in Table 2 are following these approaches. The heterogeneous network which includes such objects is part of a growing concept called Internet of Things (IoT) (Stojkoska & Trivodaliev, 2017). This approach, combined with smart meters, can transform homes and offices into energy-efficient and smart environments. Table 2. Summary of some of the networking technologies used in IoT (Kailas et al., 2012)

One may raise the question why there are several network technologies deployed, or why is there not only one solution embraced and promoted by researchers or the market. While the question may be answered from different points of view (some of them also discussed in this thesis) one of the reasons is that every technology is focusing on different aspects, which are tackling different issues and covering specific use cases. For instance, one solution is focusing on low power consumption (e.g. ZigBee or EnOcean) while others offer more data transfer speeds or more securities. The expected explosion in the number of connected devices and IoT services, along with different cloud architectures and AI solutions will inevitably lead to excessive network load, end-to-end service latencies, and overall power consumption (Barcelo et al., 2016). Consequently, developers and researchers are starting from an existing layer-based model, like the well-known OSI model, and are modifying it with the aim to achieve different solutions with specific strengths. In fact, they are simplifying different aspects or they even omit some of them completely. This is done because in most of the cases the full network stack is too heavy for different hardware, tasks and use cases, hence causing network and microprocessors overload. Reducing of these layers to basic functionalities is also one of the reasons why different solutions lacks better security, as this work comprehensively discusses in chapter 9. To get a glimpse on the complex and diverse concept of IoT, (Li & Yu, 2011) presents in Fig. 1Fig. 13 different layers in the context of IoT based on the OSI model. Al of these layers can impact the efficiency of IoT systems.

Fig. 13: The layers of smart home applications in the context of IoT (Li & Yu, 2011) Among all these technologies, some systems gained more attention. For instance, ZigBee based systems are popular due to their low cost and low power consumption (Krishna & Dharma, 2017) & (Jaloudi, 2015). Next section will briefly present this technology, while further chapters in this work will address different specific aspects of it. ZigBee This is a WSN technology whereby a network of devices can transfer the information from one device to another, while the information is gathered from a monitored field. The data is forwarded via gateways to multiple nodes. In this technology, the data is connected to other networks using wireless and ethernet links. Based on the operation of Wireless Sensor Networks, it consists of base stations and various wireless sensors in order to propel the signals to various nodes via a line of site. These components may be implemented using different network topologies such as star, tree and mesh topologies.

ZigBee is an implementation of the IEEE. 802 standard family, more precisely the IEEE 802.15.4 standard. This wireless technology is primarily built for the connection between control and sensor unit. In fact, it is not very different from the Bluetooth and the Wi-Fi approach (Withanage et al., 2014). The standard specifies for this technology the frequencies 2.4 GHz, 900MHz and 868MHz. One further important fact about ZigBee is that it is designed for low data rate, low level applications and it is an open standard. The standards used here are maintained, updated and upgraded by the ZigBee Alliance. For instance, in order to boost the IEEE 802.15.4 standard, Zigbee added security as well as network layers in addition to the application layer. Based on this Wireless Sensor Network technology, there are 3 major ZigBee Specifications which include ZigBee RF4CE, ZigBee PRO and ZigBee IP. For the case of ZigBee RF4CE, it is purposely designed for the simple two-way device to device application control which do not require a complete mesh networking functionality that is offered by the ZigBee specification. ZigBee PRO aims to provide the basis for Internet of Things with features to support low cost and high reliability for network communications. The PRO specification allows for instance advanced web service interfaces such as the simple object access protocol (Jaloudi, 2015). Further, it also offers Green Power, which is a feature that supports the harvesting of energy for self-powered devices similar to the EnOcean technology (see 5.2.b.) Wireless Systems). The last ZigBee specification is ZigBee IP which is used in optimizing the standard for IPV6 based wireless networks.

3.5. The Home Energy Management System HEMS

As further chapters in this thesis often refers to this concept implemented in smart homes, abbreviated as HEMS, following should give a brief overview over the purpose and the responsibilities of HEMSs in domestic spaces. Basically, HEMS is an energy centered approach for smart homes, meaning that it aims to manage and efficiently control everything related to energy production and consumption in a house. Based on the technological advancements and available regulations which relate to the environmental issues, SH applications progress into HEMS-applications which are not only to offer the conveniences and ease, but also to monitor, control and to make efficient-use of energy at home, hence reducing high quantity of power and the electricity bill. The energy efficiency is reached by focusing on opportunities for reducing energy consumption or avoiding its wastage. At the same time, it is aimed that human’s involvement is kept as low possible in this process (Zhou et al., 2016), in order to avoid his distraction from other life and social relevant activities. One key element for achieving this is by using AI and intelligent energy planning algorithms, which will enable residents to make optimal choices about how to spend electricity to reduce energy consumption. Further, in smart grids, the introduction of HEMS gains nowadays more importance, as this cooperation will allow a balanced distribution of the energy generated by users according to the prices of the energy, which is regulated by daily rates (Lobaccaro et al., 2016). Another feature trend will then be to move from daily rated pricing system, to more dynamical pricing plans, as further discussed in Section 5.2.a.). To achieve such functionalities, HEMS applications are dependent on several internal and external input data, and at the same time they need to be able to access and control part of the components of the smart home. The diagram below shows the components forms the environment of HEMS (see Fig. 14). Furthermore, because all this information accumulates in a central place, the security aspect of such a system should not be neglected. Based on these facts (Zhang et al., 2012) extends the idea of HEMS suggesting an “information-centric approach to secure home energy management” called iHEMS.

Fig. 14:The environment of HEMS (Santoso et al., 2018)

3.6. Summary

In order to define a basis on which the next chapters will be discussed, this section presents a brief overview over the most important aspects and variations of smart home technologies. First, the main components of a smart home were presented, by categorizations as literature suggests it. Subsequently, a general breakdown of the components based on their technical ability and their purpose(s) was proposed. In order to build a complete functional smart home system, these components can be interconnected in different ways to achieve specific structures. The main approaches to achieve different system architectures including their strengths and weaknesses were then presented in the following three sections. As the latter two sections present the most implemented approaches nowadays, each of these sections also present one of the well-known relevant technologies. Finally, the concept of HEMS was briefly presented, as it is an important approach, that can greatly influence the usability of smart home systems, as it will be discussed in the following chapters. Furthermore, different subjects of this thesis will refence to this method, aiming to discuss its strengths and challenges.

4. SOCIAL IMPACT AND RELEVANT TARGETED GROUPS With advancement in technology and modern means of communication and information, technology has reshaped every habit of humans ranging from social, political, professional, economic and personal life. There are several factors which have been affected by the use of technology in every walk of life. Now the biggest concern of human is to be updated with ever-changing demand for technology and innovation. Like in every case, this advancement has also engulfed the old living style and now the homes are also shifting on technology in order to make humans lives more efficient and meaningful. However though, from a more critical point of view (Hancock, 2014) even goes so far in trying to find an answer to the question whether there is too much automatization in our era, and whether the unlimited possibilities of automation will maybe turn out to have an negative impact on the quality of human life. A smart home is set up according to the wishes and needs of the owner; hence it has to be designed in a user centered design. A contemporary smart home device is a voice assistant, a personal helper that ‘lives’ in one’s phone, tablet, and speaker, streaming box or other internet-connected devices. A smart thermostat that allows to set the heating to turn on before one comes in from a freezing winter day. Although the consumers are very enthusiastic about smart homes, there still remain issues which lead to the fact that only a few people in the world are taking advantage of smart homes and the social aspect may have a significant contribution to this. However, generally speaking, everybody wants to live in a smart home, which ultimately would improve the life quality, as stated by (Aiello et al., 2011). But when talking about smart home systems, most of the researcher are focusing on technical issues and approaches, while the personal and the social consequences of this technologies, which are also a key to the success of these solutions are not very well discussed (see for instance (Gergely, 2018) or (Cook, 2012)). Another reason for the technology’s relevance in social domain lays in the fact that a “home is not only a technical space according to each individual’s role but also a social space where family members interact with each other” (Lee et al., 2017), so it is important to ask ourselves when technology is improving natural social aspects or it is disrupting them. One research which aims to identify and proposes removing of such various ‘social barriers’ is that of (Hargreaves et al., 2017). This chapter addresses the social implications of smart home systems. It tries to give an overview of the impact of these systems in the daily life of consumers who are using them. In the second part it presents, based on research and case studies, findings about the relevant target groups which are likely to use such solutions and what are the likely reasons for limiting these technologies to be used to a larger scale: Is it because of the affordability issue or the complexity of these solutions? Or is this even a cultural issue?

4.1. Impact on Human-Computer Interaction and Behavior

The social impacts of the smart homes can easily be understood looking for instance at following use case: The physical impaired people whose living has been redefined by SH technologies. Healthcare providers are trying to find ways to support more people at home, finding home care workers and the money to fund this help is not easy. In such a situation, a smart home is helpful. Users can avoid their helpless by making use of it during their illness. This is possible because a smart home can be designed according to the needs of the sick people. This further leads towards making them independent enough, so that they may do their daily chores and activities themselves without depending too much on the attendants. Many devices can be deployed to help them, such as mobile phones or electronic sensors that sound alarms in emergency situations. The healthcare provider can than observe and assist such sick and disabled persons directly from the clinic. They can retrieve information how patients are progressing in their homes and then make decisions about their care. Some smart home technology also provides the security system of a home. Consumers purchases various security devices to make their homes safer and more secure. There are motion sensors which are installed in doors, windows or at any entry point. Similarly, security cameras also provide the same facility in a improved way. Smart locks is another technology that can be used in different places for different purposes. For example, you could set your smart locks to turn on your smart lighting when you unlock the front door. By using this type of smart, time and energy can be saved.

At the same time, smart homes do not only impact or support the individual alone, but also the human-to- human interactions. To offer a clearer picture on this subject, (Lee et al., 2017) suggests that there are two types of social connectedness supported by smart homes: Firstly, the Inner Social Connectedness (ISC) that is generated through connections between the user and the devices in their smart home; And secondly, the Outer Social Connectedness (OSC) that is generated through connections between the user and the SH devices in other people’s houses. The Inner Social Connectedness acts between the user and smart home devices positively and influence the perceived social support (PSS) in context of SH. A user of a smart home is expected to enhance its connections inside the home, and he can perceive social support by interacting with smart home devices because, as CASA (computers as social actors) studies have shown, human-machines interaction is as same as human-human relation and connection. And in other words, ISC can be increased by sharing situational information between SH devices and users. Similarly, the outer social connectedness can also be enhanced through making connections with the humans outside the smart home. A user can acquire the social support through his family, friends and relatives who do not live him in the smart home. The effects can be than increased by sharing information between SH devices outside home. Thus, users can experience a feeling of connection with friends, family or relatives while sharing data with them or while observing different smart home related data from their homes. And last but not least, as (Thiebaud, 2010) mentions, in the face of worrying statistics about more and more cases for depression, smart home technologies can provide emotional satisfaction with a feeling of control over his life. These are just some use cases and the list is far from being exhausted. So, expectations from smart homes are clear and versatile, and also the motives of users are various, depending mostly on the context of the individual's life. But the fundamental aim is either to reduce the difficulty of challenges in a human's life or to enable more comfort and to take advantage of more luxury by sustaining the basic necessities of life. In fact, (Satpathy & Mathew, 2007) mentions one of the classical definitions for smart home which concludes in a concise way the aim and expectations from a smart home. Such a home ‘is smart enough to assist the inhabitants to live independently and comfortably with the help of technology’. However, all these expectations cannot be fulfilled by real world solutions if designers do not have a clear understand of the human behavior and their needs in different situations. For a smart home to support its user(s), it must recognize or at least be programmed in accordance to their behaviors. For instance, as (Gazzawe & Lock, 2019) states, people always prefer simplicity and efﬁciency around them. They look for relaxing while other operations which they would have otherwise done performed manually, are automatically facilitated through using SH appliances (Gazzawe & Lock, 2019). However, to automatically understand and to adapt to different behaviors is a slightly complex task for algorithm designers and solutions for an automated occupant’s behaviors recognize are nowadays not yet available on the market. Yet, an actual research artifact is for example the one suggested by (Chua, 2017). Likewise, case studies findings from (Davidoff et al., 2006) suggests that “more than control of their devices, families desire more control of their lives”. Consequently, researchers and designers should shift from an end-user programming perspective to a wider view, where home control does not include the control over just technological systems, but also control of the things families most value – their time, their activities, and their relationships. Davidoff also makes an interesting remark that by just extending and increasing the functionalities, this can “easily overstep some invisible boundary, making families feel at the mercy of, instead of in control of that technology”. A similar concern was also a identified by (Oliveira et al., 2015) who interviewed 16 households before they installed a smart home system for the ﬁrst time and when they had to make key decisions such as which devices to install, and where and how to position them. Among other difficulties diagnosed through this process, some issues were related to design aspects of acceptability and usability and complexity in homes. The report of (Hargreaves et al., 2017) was not very different either, after a conducted study, the author conducted that the users found the cognitive and practical work of accommodation to smart home technologies very challenging.

4.2. Target Groups

Everything that is made by human or any activity that is draft out, there is always some targets group which need to be focused in order to justify the productivity and activity. Same is true with the smart home technology. The need to understand the target group of the smart home technology is essential this will help in making and integrating the technology to cater the need of users. Based on the conducted research and the available functionalities, 4 target groups will be listed, accompanied by further arguments for this classification. Yet, it is important to mention that such SH systems will be adapted to the targeted group itself, as one system should not cover all functionalities for all situations, as it will be inefficient and costly. Early Adopters – New Technologies, New Playground As almost with every new technology, smart homes targets and in fact need or asks enthusiasts and who are willing to try and test new solutions and approaches which will shape the future. Only by this means such technologies can became robust. Even if smart homes are not new, the methods, approaches and efficiency is constantly changing, so it still need this group of people as it still didn’t attract a large public scale (see also 4.3). This target group was also identified in other case studies like the analysis done by (Shin et al., 2018), as being currently the most relevant one, because they also help to overcome demand stagnation until popularized. Sick and or Elderly People – Care and Support Regarding care and supportive services, smart home targets elderly. It can also be useful for older people who are not given any special facilities from the government (Nygren et al., 2005). Similarly, those who are disabled and infirm can also be targeted via smart home technologies. This technology offers for instance a medical alert bracelet that is effective in difficult situations for older and or disabled persons. Furthermore, this technology is able to provide comfort and entertainment for this target group (Lievemaa, 2018). Such type of smart homes can also be called telecare networks as suggested by (Saito & Menga, 2015). In this context, a sample eco-system application is shown in Fig. 15.

Fig. 15: A sample telecare network (Saito & Menga, 2015) 28

Closely related to this target group, are those who live alone. As Epley (Epley et al., 2008) also proved, people who lack social connection with other humans tend to rely on nonhuman agents, such as animals and gadgets, so smart home systems are very effective to overcome loneliness. Dual Income Families – Time and Schedule management Households in which both partners are employed is another target group, which was as also identified by (Davidoff et al., 2006) in his case study. These families represent an interesting population for several reasons. First, at 43% of the population of the United States and growing, dual-income families represent a significant demographic whose sheer magnitude merits attention. In addition, dual-income families show a particular need for support. By moving away from the single-income model, these families are exposed to a surprising variety of stressors. Taxing schedules and no anchor presence at home impose particularly high coordination costs. Parents are also exposed to role strain, where they feel pressures in trying to comply with the expectations attached to their roles as parents which adds to an already stressful existence (Davidoff et al., 2006). Being in office, one can think a lot of issues about the house that can be distressful. Such thought can be for instance: Did I turn off the coffee maker? Did I lock the main door? Did I turn off the lights? There are many similar questions that are wandering in one’s mind and can trouble at work. Smart home technology plays an important role in eliminating all these concerns. This can be avoided by connecting the smartphone and tablet to the own smart home and making sure that systems or devices at home are in the desired state. Single Persons – Personal Home Assistant Single person household is another target group for that advancement. If one person hast to manage both handle both home and business, then smart home technology play a beneficial role in making tasks easy and less-hectic. Such technologies enable the warm up of the house before waking up in the morning, for instance, and it this keeps the user updated about home events, even when he is not at home. More contemporary solutions (and in the future more and more available) would then also assist the home owner with ordering of products and even their delivery when he is away. Wealthy Persons – Comfort and Entertainment The last relevant target group that is the class of rich people. These users deploy smart home technologies for their comfort and entertainment. People of this target group are important because they are able to spend high amounts of money on such technologies, which enable relaxation and comfort

4.3. Smart Home as a Social Disruptive Technology:

The term disruptive technology is first used by Harvard school of business (Dutton, 2014). Disruptive technology, lacks refinement often has performance problems because it is new, appeals to a limited audience, and may not yet have a proven practical application. Disruptive technologies typically involve a high rate of technology change, broad potential scope of impact, large economic value that could be affected, and substantial potential for disruptive economic impact. Smart homes can also be regarded as a social disruptive as due to its ignition at limited scale, it has been unable to attract a large portion of the public. Where the homes have been established, their impact and limitations obviously are there. Connected homes will alter the family dynamic as less time will be spent on menial household chores. This connectedness minimizes human’s interaction with others as home technology tends to sometimes occupy the human’s role. Further, the accommodation to new technologies can be very distressful and weary, at least in the beginning, as reported by (Hargreaves et al., 2017). In the same report one can also recognize a further socially disruptive factor; as there are sometimes members in homes which are more technically competent than the others, there is a potential for tensions as these members are seen as those who may try to take over the home control (justified or not). The conclusion of the same report was that smart home technologies are both technically and socially disruptive; and smart homes require forms of adaptation and familiarization from householders that can limit their use; Even if not under the term of social disruptiveness, (Hindus, 1999) discusses about three factors that can be assigned to this topic. They have to be considered in order to avoid alteration, or dysfunctions of social life in the process of technology domestication: First aspect is that “homes are not workplaces”, meaning that unlike workplaces they do not have professional planning, installation and maintenance of technology

29 and infrastructure available. The importance of the maintenance aspect will be discussed more extensively in section 5.3. Furthermore, it should be considered that households are not including only working age adults, but also elderly people, children, babies and pets. Second principle that cannot be neglected is that “consumers are not knowledge workers”, hence householders are interested in aesthetics, fashion and self-image and their motivation is less focused on purchasing from a productivity perspective, as it is the case of workplaces. The third aspect stipulates that “families are not organizations”; meaning that decision- making and value-setting are quite different between the two entities. Further, she states that families have a different structure than the corporate organizations.

4.4. Conclusion

In the end, with all its glamour and prodigious impact, smart home technologies can improve and uplift the life style of theirs users, no matters at what scale they are using them. But all this advancement is not as smooth and comfortable as it seems. Along with all the benefits, this smartness in homes is also promoting social disruptiveness for humans, as their main way for communication and interaction is left with and through devices. The role of the smart technology can be accepted as a change agent in human life when it will anticipate and respond in the home premises. In order for smart homes to achieve their promise of significantly improving the lives of families through socially appropriate and timely assistance, they will need to sense, anticipate and respond to activities in the home. Therefore, it would have to appropriately respond to eventualities of deviations from the plan. But at the same time, if the system gets to diversified and complex, this will eventually lead to more confusion and more disruptive factors. The dependency on smart technology will not only reshape the human behavior but it is also making its way to take up the family reasons to interact with members and making humans dependents of devices to perform home tasks.

“Smart homes will become a reality when able to improve the quality of life of their inhabitants without forcing the users to change their behavior or give up their control of the home. To reach this goal research spanning from engineering to the medical arena going through sociology and the theory of computation is necessary.” (Aiello et al., 2011)

5. ECONOMY - SHORT- & LONG-TERM COSTS This chapter discusses the economic aspects of a smart home technologies, both in the investment phase as also while the operation time, through maintenance. These however may greatly differ between technologies, as the findings will show in the following points. First section will discuss about purchase costs regarding different systems. In terms of usability two main cost points can influence it: (1) the energy costs induced and spared by smart home systems and (2) the maintenance costs.

5.1. Material & Investments Costs

When talking about installing a smart home, two aspects must be considered: hardware and software. The hardware is needed for several indispensable functions: sensing, moving and interacting with and within the physical world (see also section 3.1). Thus, one cannot reduce smart home to software solutions only. At the same time, specific system solutions must communicate with each other through a network as explained in section 3.1 number 4. In most of the cases however, Software (programs, applications, algorithms) and Hardware work hand in hand and they cannot be separated. Therefore, when talking about material costs, all these aspects must be considered, There are a variety of solutions available, as well on the market, as also at the research level, and all these solutions differ greatly in terms of costs. However, based on the research conducted, it can be said that most of the researchers are focusing on low to very low costs solutions, at least for the prototypes. For instance OSGi, which is free of charge use (see also 7.1.a.)is considered as the leading architecture in terms of research-oriented smart homes (Leitner & Harper, 2015). The market on the other side, is focusing on developing robust solutions which in the end are costly and not affordable by everyone. However, based on one company I’ve interviewed (see section 2.2), the interviewee estimated that investment costs should be not more the 15% higher for smart homes than for standard powered homes. One interesting finding I should mention here is that, as far as my research and case studies reached, there is almost no difference in the functionality of the systems themselves; Low priced systems can mostly offer the same features as the expensive ones, because, in general, the technology and smartness potential of them is similar in both cases. The big difference however lies in aspects like after sale support, user friendliness and level of easiness to deploy. In following, some representing examples will be presented, as well from the low-cost domain, as also from higher price class. a.) Low Cost Systems It can be said that systems can be inexpensive mostly in two circumstances: (1) when the design and implementation is conducted based open standards, and thus no costs are involved for licenses or for a design from scratch; or (2) when vendors are trying to push new systems on the market, aiming to address new customers. The first case is especially interesting, as it also promotes the use of already existing standards. This also leads to the fact that vendors can make use of the present best practices and R&D can be reduced to a minimum. (Davidson et al., 2018) presents for instance a SH solution which is completely based on Open Platforms, by using Arduino, Raspberry Pi, NodeJS, and MongoDB. When considering the hardware costs the price for an Arduino or Raspberry Pi can be as low as $50. Further, a basic sensor can cost bellow $10. In contrast to a commercial solution, where an intelligent sensor can cost several hundred euros, the Arduino- +-sensor-combination is justified to be considered as inexpensive in any case. The main challenge here, is its installation and integration in a smart home system, as these solutions mostly offer a skeleton and the needed tools for further specialization depending on the use case. For this, one either must be technically skilled, or he has to hire professionals for the installation phase at least. Likewise, the solution by Davidson et al. is not yet marketable and the suggestion must be interpreted most likely as a case study and a proof of concept. But there are also completely mature and operable systems that were built on this ideology. For instance (Gergely, 2018) reports comprehensively in her writing about such a smart home. There are also inexpensive commercial solutions intended for different use cases. If one would only look for the cheapest solution on the market, this would be the X10 system. According to Withanage’s research, a basic system would cost around $170. however, this system is obsolete because of its technology and performance (Withanage et al., 2014) and will therefore not be considered as a viable solution in this thesis.

EnOcean on the other side can be easily installed anywhere for user’s ease which significantly save the installation cost up to 40% (Asadullah & Raza, 2016). However, the costs can greatly increase, when deploying it in a more complex and massive project, as every endpoint needs a special wireless coupler (Aschendorf, 2014). Further issues arise as soon as one user needs more complex configurations with higher performance and possibilities for interoperability, because EnOcean is very limited regarding these aspects. In contrast to this (Withanage et al., 2014) argues that from a performance-affordability tradeoff perspective, ZigBee would offer more advantages like an open implementation standard and higher performances. Concluding, it can be said that there are also commercial solutions available, but one must take into account performance and interoperability aspects, as such systems use protocols which are not directly compatible with IoT systems, so gateways have to be deployed. Regarding HEMS, there are solutions available which are said to work with plug-in devices directly at power point, so called smart plugs. Such devices can cost upwards of $20 and are not hard to install and manage (Potter, 2017). However, as discussed in section 6.2, studies have shown that in terms of energy and cost savings they can be counter-productive. b.) High Cost Systems Two of the systems that are considered as the more expensive solutions (for instance by (Aschendorf, 2014, Leitner & Harper, 2015) or (Benediktsson, 2009) are the KNX and LON based systems. These can be seen as the luxury segment of smart home automation as they offer several advantages over the other systems mentioned in the section before. They have for instance a high product portfolio, KNX being implemented and embraced by more than 120 manufacturers worldwide. Another advantage offered by these systems is the native multiple transmission mediums supported: powerlines, fieldbus cables or wireless. In contrast to it, EnOcean or Zigbee for instance are operating only through wireless channels. Through the diversity offered by these systems, another luxurious aspect is well integrated in this solution, namely multimedia and entertainment. This is accomplished through all in one multiroom facilities, well thought-out designed graphical user interfaces and different connections to third party infotainment utilities. However, this does not mean that such features are not available in cheaper systems. In this case, one has to invest more time with self-adapting to reach the similar results, as those of the expensive systems. But as already mentioned, this comfort and flexibility comes at a price. As (Aschendorf, 2014) estimates in his book, such a fully customized smart home is targeted for villas that come around 500.000€. Furthermore, maybe, one of the most challenges with these systems, is the retrofitting problem. As these systems operate on decentralized architecture (mostly) by means of fieldbus wires they are in most of the cases only justified for new built homes. At the same time, the needed amount of cable should not be underestimated. Based on personal experience, several hundred to more than one thousand meters of twisted pair fieldbus cable for a single-family home has to be planed.

5.2. Energy Cost

Energy consumption reduction is one of the aims of smart homes. But if the smart home system itself causes a further energy consumption, which in the end is greater than or equal to the energy savings achieved, than this technology has missed his goal. However, it is rather impossible to compare this to subjects and to conclude to a general answer which applies for all cases out there. This chapter talks about these two aspects: (1) energy savings and (2) energy consumption induced by the smart homes. a.) Reducing Energy Costs As mentioned in section 3.5, HEMS is the heart concept in achieving energy saving and thus reducing the costs. There are different tools and concepts to reduce energy wastage or energy costs. (Zhou et al., 2016) report that based on different studies the operational cost of electricity can be reduced through load shifting by 23.1%. Further, (Baraka et al., 2013) state that the application of home automation systems can save up to 30% of the energy without compromising comfort. The question is however, if this can also be applied in general and with every occasion, as research suggests that there is doubt in the potential energy saving. Academicians argues that energy consumption does not only depends on the technical solution, but it hardly depends on structural, followed by socioeconomic factors and behavioral factors (Kavousian et al., 2015). For instance, the type of family inhabiting a house has a significant impact on the HEMS efficiency.

In the following, further two important factors, which can influence the performance of HEMS will be discussed. Lack of appropriate price plans To enable HEMS to use their load shifting ability, energy provider must provide the infrastructure (smart meters) and flexible pricing plans. Table 3 shows that energy costs in smart homes with HEMS can highly depend on the Demand-Response (DR) pricing plan. (Zhou et al., 2016) also shows that between two pricing plans, the energy saving can greatly vary (costs reduction of 9.8% with a more static plan but still flexible, in contrast to 28.3% with another, more dynamically price plan). Otherwise, if the pricing plans are fixed/static, all the load shifting concepts are useless. In the case studies I was involved, there was no electricity supplier who offered such flexible price plans, because the houses, even if newly built, were not equipped with a smart meter (while smart meters are the first condition for this feature). As far as I am aware of, now there is only one type of DR pricing plan available in Austria (besides the flat rate plan) and this is the day-/night-based price plan. However, the information I got after discussing with one of the electrician companies involved in these case studies was that the energy suppliers are thinking about such dynamic plans or they are working on this already. Nevertheless, it could be a cost-effective investment to equip houses with such technologies, if planning to implement a smart home. By doing so, one is prepared for these options as soon as these will be available on the market. Table 3. Comparison of Residential DR Programs principles (Shareef et al., 2018)

Unpredictable behavior and schedule changes Most of the HEMS scheduling solutions were designed based (1) on the premise of routinization and (2) by assuming that users will obey and learn to use and adapt their behavior in favor of the energy saving life style. One example of such a solution is suggested for instance by (Alimi & Ouahada, 2018), concluding that based on tests “energy consumption can be planned, monitored and controlled to avoid energy wastage”. Other solutions by (Kalezhi et al., 2018), (Xia et al., 2018), or (AlFaris et al., 2017), to mention a few, suggests also similar approaches, which result in high saving potentials. Nevertheless, the reality shows that this is often not the case, as at the same time other researches and case studies concluded. The prediction done by the artificial intelligence of HEMS is done assuming that users of smart homes develop in daily life a fairly stable routine. Nevertheless, the aspect of routines for enrichment activities,

33 which prove to be difficult to construct, are often neglected, as (Davidoff et al., 2006) concludes in his research. He further discusses that also not planned breakdowns in daily schedules are difficult to predict or react on them, and last but not least, scheduling systems often do not efficiently react on seasonal changes. The other aspect of inefficiency of schedules due to inappropriate behavior has demographic, education and awareness correlation, as the case study of (Kavousian et al., 2015) shows. (Lobaccaro et al., 2016) also concludes that even the cost saving potential through DR based pricing plans is greatly influenced through users’ behavior. In a study conducted in Denmark it was found that in the 290 identical homes that were investigated, the heat consumption differed by 20 times between the lowest and the highest in the ranking. The reason for these big differences was concluded to be because of the user’s behavior (Valentina et al., 2012). One reason can be for instance, if users have doubt that such systems can help them in saving energy, this will lead to lower efficiency of HEMS. Consequently, case studies show that there is a need to educate users and to raise awareness regarding the lifestyle impacts on eco- friendliness. Further, the behavior is also highly influenced by demographic factors. Retired people, for instance, have another lifestyle as dual income family. This leads to different load shapes as Fig. 16 shows it; While households with users at home during the day show small peaks of loads more often in the afternoon, the other have the highest consumptions peaks in the morning and in the evening.

Fig. 16: Daily load shapes over different two days (Kavousian et al., 2015) Consequently, it can be concluded that one scheduling algorithm that can cover all use cases if it based on a single normalized load, based on a general statistic. These have to be chosen or adapted based on the user and his lifestyle. (Chua, 2017) suggest for example an algorithm that is able to recognize the behavior and thus identify the appropriate scheduling strategy. b.) Increasing Costs Through Consumption? As smart home technologies are powered through electricity, they will also cause an additional energy consumption. As mentioned in the introduction of this section, if the energy costs caused by these systems increases more than the saved energy, than the advantage of energy saving though smart homes is nullified. Based on different investigations and test experiments collected, (Wisser, 2018) reports that the energy costs caused by smart home systems made up between 7% and 15% out of the total energy cost of the house. If we than take one of the less efficient results regarding energy saving reported in previous section (a.) above, namely 9.8%, than it is appropriate to mention that in specific constellations it can occur that the effective energy saving is zero. The power consumption for smart homes devices depends however highly on the different technologies in use. In the reports above, it was not specified which technology was used in the experiments. Further, the settings of the devices and how data processing is done can have a big impact on the consumption. Following three sections discuss aspects which influence the energy consumption and thus the usability of the smart home systems. Data Processing & Device operation Even if a low power consumption system is deployed, there are opportunities to even lower the consumption, or if done wrong, to increase it for not justified reasons. For instance, local computation is

34 an operation cheaper than communication (Stojkoska & Trivodaliev, 2017). A prime example would be the temperature measurement: As temperature is not a fast-changing variable, it is inefficient to send the temperature value every second to the network. A better approach would be to build the mean value of the temperature directly at the sensor and to send it in bigger periods (e.g. every 5 minutes). Another approach would be to operate the device at full power only when sending or processing data. Such an approach is for example natively implemented in the EnOcean technology. This idea is justified for different sensors and components which do not have to stay continuously awake, but only at predefined intervals, or when an external interrupt (e.g. pressing a button) is registered. Thus, protocols can be set up to control power save modes and wake-up mechanisms of each node (Saito & Menga, 2015). Further, as some devices are equipped with more features, interfaces or even sensors than actually used, they can be tweaked to reduce their consumption by completely disabling the unused peripheries of that specific smart device. Wired Systems Proven SH systems like KNX were initially defined to communicate only through wires, and even today, it is the preferred way to deploy wired systems, if possible. According to (Benediktsson, 2009) 90% of KNX buses are of this type. The argument for wired systems is given by more stability, reduction of interferences (in contrast to RF systems), and increased security, because in a wired system, data cannot leak outside the walls. Wired systems can be deployed by means of power lines, fieldbus cables or in a completely IoT- equipped house, just by network cables. The power consumption of decentralized smart homes is proportional to the house size, as any node in the system will need to be powered in some way. From one of the case studies related in this thesis, following findings were made: - KNX technology was used for all three floors. - Almost 45 KNX devices were installed. - During construction more than 1500m of fieldbus cable was installed. - The designed power supply for the KNX system was rated to deliver up to 640mA. - For testing purposes, a power supply with only 320mA was tested but it failed to deliver the demanded power. Later the actual power consumption was measured: ~450mA at 30V. - Consequently, the complete KNX system has an average consumption of around 13,5W. Based on the KNX standard, specifying that a KNX unit is not allowed to consume more than 200mW (see 3.3, EIB/KNX Based Systems) and the fact that there were less than 45 devices in operation, the maximal consumption should theoretically not exceed 9W (0,2 * 45). The cause for the additional 4,5W measured, comes from the consumption through the wires, as every wire is a consumer itself. As the system hast to be constantly powered on, the average demand of energy in a year can easily be calculated and it sums up to be ~118.3kWh. Based on the average consumption of a five-person household in Austria (~6803,9kWh (AUSTRIA, 2019)), powering of the smart home technology alone, makes around 1,7% of the total energy cost of the household. The result seems to be satisfying enough. However, this are roughly estimated values and can vary depending on the usage of the system. In order to calculate the worst-case scenario, the same calculation was done with the maximum rated power consumption, 640mA, as it is guaranteed that this limit will never be exceeded. The consumption in this case would be ~168.3kwh/a. To make the calculation even more conservative, from the same statistic, the average power consumption for a general household (regardless of its size) will be used (3559,9kWh). The result in this case is around 4,7%. So, even in this case, the result will be still lower than the results reported by Wisser, mentioned in the section introduction above. Thus, it can be concluded that this wired system has a reasonable low energy consumption, which will not exceed the potential energy savings facilitated by the same technology. Wireless Systems As the field of IoT is growing, also the wireless solutions, WSN are getting more relevant, especially those aimed for low power consumption. Some approaches to lower the energy consumption in WSN include: (1) selection of low-power components, (2) use of improved wireless, (3) protocols and (4) adapting parameters such as clock rate or sample rate (Magno et al., 2010). Consequently, different technologies were designed based on these principles. Some examples will be discussed here in terms of energy consumption and are shown in Table 4. 35

The first listed technology, WiFi is well known and widely used for different appliances, not only for smart homes. In fact, it was just taken directly without any adaptions into the smart home domain. This is the reason why it has no lower power consumption focused implementation. If the case studies case mentioned above would be implemented by deploying WiFi devices instead of the actually used technology, namely KNX, the power drain for the whole wireless system would reach in worst case around 35W. Based on the same estimations above, this would make up around 8,6% of the total consumption of the household in a year. In contrast to other technologies, it has much higher data rates and a high adaption rate on the market, but as the speeds are not that relevant for this use case, it can be concluded that is not the most suitable solution for smart homes. It can be however used at a higher level for data transfer between groups and areas of buildings, but at the sensor level. Another reason for the same conclusion is that hardware has to support a rather complex and heavy protocol. Thus, it is more expensive than its competitors. On the other end of the list is the EnOcean technology; It drains no electrical energy from the house system, as it efficiently exploits applied mechanical excitation and other potentials from the environment (motion, pressure, light, and temperature) using the idea of energy harvesting order to transform such energy ﬂuctuations into usable. So, even if this system would be the most efficient in terms of energy costs, other drawbacks makes it not widely adopted (Lobaccaro et al., 2016). This includes lack of standardized protocols, short transition ranges and a slightly higher purchase price in comparison to similar technologies. ZigBee can be considered as a tradeoff between the two ends of the list, discussed above. In fact, it is an adaption of the Bluetooth protocol which supports longer ranges and higher data transfer rates, with a slightly increase of the power consumption. Nevertheless, the energy demand for this technology is still held very low, thus achieving lower consumptions than a wired system. Based on the same case study discussed above, it can be stated with certainty that a system at the same size and number of devices, would not require more than 8W, thus being a part of the complete energy consumption of the house only by 1,7% in the worst-case scenario. Table 4. Comparison between wireless protocols (adapted from (Jaloudi, 2015)

In order to operate the smart devices completely wire free, small batteries can be used for every node. ZigBee is just designed with this aspect in mind (Withanage et al., 2014), offering operation times with a single battery for multiple years. In conclusion, it can be said that there are low powered solutions, as well for wired as also wireless solutions. Therefore, energy costs incurred by smart homes systems should not be seen as a crucial concern when addressing the usability of smart home systems. Choosing the right actuators I made an important finding, while analyzing this issue at two of the case studies I was involved in: It makes a huge difference, how loads (e.g. lights) are controlled, hence what actuators are deployed and how they are operating. The focus here is especially on the contactors; basically, there are two ways to close and open an electrical circuit by contactors: through monostable or bistable relays. Monostable contactors would return to the initial state (open or closed, depending on the model) as soon as the control circuit is powerless. In contrast, bistable contactors react on an impulse on the control circuit by switching their state (e.g. it switches to open if it was initially closed). The main difference here is that a monostable relay would consume electrical power as long as it is activated, while the bistable type ‘memorizes’ the state from the last impulse, without the need for further power. I could clearly see the contrast between these two approaches, because one project I was involved in was using bistable contactors, while the other was using monostable contactors. Next few insights in the projects will clearly show the big impacts of different actuators: The use case discussed in section ‘5.2.b.) Wired Systems’ uses bistable KNX actuators while the second one deploys the more common and simple monostable contactors. It is important to discuss the consumption occurred by the monostable contactors, as they will drain energy as long as they keep the circuit closed in order to power on a light, for example. Next calculation will be done for the worst-case scenario: - Based on the specification sheet of the monostable relays in use, one unit consumes 500mW while activated. - The project in question uses around 60 contactors in order to control different loads. - Further, around 35 KNX devices were installed. - If all contactors would be activated at the same time, this would lead to a consumption of 30W. - If all contactors would stay activated the whole year, the average energy consumed will be almost 263kWh. Based on the household consumption statics mentioned above, actuators would contribute almost 7,4% to the total consumption. It is important to note that this does not include the energy demand of all the other smart home components in the house. If we further take the worst-case scenario and add the maximal possible consumption by the KNX devices (<=200mW), this would add an extra energy demand of 7W, hence increasing the consumption contribution of the total control system by 9,11%. One could argue that this worst case may never happen, therefore the numbers are not reflecting the reality. But even if the consumption caused only by contactors is halved to 3,7% (from the complete household consumption), the energy demand is still relatively high, in comparison to the demand of the other smart home components, which is about ~1,7%. Concluding this aspect, it is crucial to investigate what type of actuators will be installed, as they can be the cause for breaking the promise of the energy efficient homes supported by smart home technologies.

5.3. Maintenance Costs

As with any technology, there exists a lifecycle process for every technical product and smart home technologies do not make an exception to the rule. Within that lifecycle, the operational costs are a major part of this process, as also shown in Fig. 17. One of the costs elements throughout the time operation are the maintenance costs. (Woodward, 1997) divides maintenance costs intro three categories: (1) regular planned maintenance; (2) unplanned maintenance (responding to faults); (3) intermittent maintenance (for major life refurbishment). There are also different approaches to address the maintenance of a technology; for instance, by increasing the planned maintenance the risk for faults decreases, thus the unplanned

37 maintenance costs are reduced. The other extreme is to run the product until it fails, thus avoiding the preventive maintenance, but with the costs of increasing faults and reactive maintenance.

Fig. 17: Stages of life cycle costs (Woodward, 1997) The best tradeoff to achieve the lowest maintenance is, as Woodward suggests, somewhere in the middle where a balance is held between the two costs. But based on studies reported by (Sas & Neustaedter, 2017), when it comes to complex home automation technologies, most people tend to dispose of broken appliances rather than repairing them. It is however hard to estimate costs with a reasonable precision, especially if a technology such as for smart home is (1) very diversified or multi-disciplinary and it (2) did not penetrate the market at a large scale (based on statistics reported in section 2.1, actual global penetration is around 9% to 10%). In fact, such an analysis would require a separate study for itself, and it would go beyond the scope of this thesis. As far as I am aware of, there is not a single study focusing especially on this topic. Researcher express at most their concern about maintenance in a vague way. The next two sections, divided as for chapter 5.1, present a brief overview over the findings regarding maintenance aspects based on their price category. The third point discusses then about general challenges regarding the maintenance which are not related the price tag of the system. a.) Low Cost Systems Smart home solutions which are offered for low prices tend to have less maintenance support from vendors and specialist. This often leads to a left alone user who must find ways to repair or upgrade his system. This is especially problematic for householders which do not have the appropriate skills for such tasks. At the same time, maintenance companies often do not offer support services or contracts for such systems as they may not be as profitable as expensive technologies. Another issue to be considered are systems with components that are powered by battery cells. A relevant example is the ZigBee technology. In general ZigBee devices use battery cells to avoid additional wires, thus making the technology more suitable for renovation projects. This leads in consequence to additional maintenance costs. As a solution to this, EnOcean devices can be deployed which are self-powered (through the energy harvesting) to minimize this aspect, so minimal maintenance is needed (Withanage et al., 2014) however, their adaption is not broad, there are not many professionals who can install and maintain these technologies There are however several advantages that speak for low cost systems; In most of the cases, there are active online communities focused on these technologies, that are based on free sharing of instructions

38 and help (AlMarzouq et al., 2005). Furthermore, low cost solutions are often based on cheap and well- known hardware, that can be easily replaced. A prime example are logic boards like raspberry Pi or Arduino which are widely adopted, and their platform is totally open. Likewise, one can also find several free utilities in the online space which are a tremendous help for maintenance task. Consequently, it can be concluded that low cost systems are also cost efficient in terms of maintenance, but in most of the cases, the user has to take care of this task by himself, as vendors often do not support these solutions. b.) High Cost Systems Expensive technologies known to cover the luxury segment offer different opportunities and vendors are more willing to offer maintenance support them, but at the same time, theirs’s users are also facing different challenges regarding maintenance. One of the convenient features higher priced systems offer, is the possibility for remote maintenance by troubleshooting companies, aided through IP based communication (Kastner, Neugschwandtner, Soucek & Newman, 2005). The advantage is two-fold: (1) householder do not have to take care of appointments with the company for maintenance on site, while (2) the company’s employees save time and transportation costs. This feature raises however security concerns that will be discussed in chapter 9 on a larger scale. There are also some costs that may be not reasonable for private uses. For instance, KNX systems must be parametrized and managed by the paid software called ETS. The software license is however expensive, and its purchase is not justified for private persons. The only option the user is left of, is to call in a company for every maintenance or minor change he needs to do. Nevertheless, this is not an issue in every case, as users that purchase expensive systems are likely not interested in learning and customizing the system by themselves, thus they are reliant on external specialists. Often systems like KNX have different diagnosis utilities which greatly reduces the time of maintenance. This was the case in one of the projects I was involved in. At some point in time, the system got unstable and there was no obvious hint for that cause. After a short inspection through the diagnosis tool offered by the smart power supply of the KNX based system, it was found that devices in the network were underpowered, hence leading to an instable communication between the participants. With proper parametrizing, such tools can even be utilized without any extra tool, because diagnosis information will be transferred to devices ability to display text messages. These features can be implemented also with low cost technologies, however the time costs for implementation are significantly higher. c.) General Challenges In the case studies conducted by (Hargreaves et al., 2017), it was found that in case systems broke down, there was a general lack of maintenance service available. This was also accompanied by too little online support and a lack of skilled plumbers or electricians. The lack of professionals is also acknowledged by (Aschendorf, 2014), as mentioned in the introduction chapter. Consequently, the costs for maintenance tend to be overpriced as the increasing demand for troubleshooting and support is not satisfied by enough companies equipped with the needed know how. The fact of low numbers of companies offering true troubleshooting services is also supported by the interviews conducted for this thesis (see chapter 2.2): Out of 10 companies that sell and install smart home appliances, only one firm confirmed to offer 24/7 troubleshooting contracts. Most of the other companies argued that the systems are stable and normally “nothing should go wrong”. From my point of view, is this argument not justified for the fact that, if a system responsible for basic functions like light or access control breaks down -as low as the chance may be- the user will be put in a difficult situation, being forced to wait until the opening hours of the company requested. Another important aspect is that the maintenance also depends on the features and functions implemented and not only of the type of technology deployed. Basically, the more complex and less common the sensing part is, the higher are the maintenance requirements. For instance, a pressure sensor needs to be periodically adjusted, in order to avoid erroneous measurements. Further, specific sensors have only a limited lifetime, meaning that after the period, they have to be purchased and installed again.

5.4. Switching Costs

As technology is advancing and new solutions and standards are emerging, other outdated systems have to be replaced. The question than arises how difficult it is to upgrade to another technology and how high are the costs. Regarding this aspect, proprietary solutions are the most concerning ones, as they are supported only by one manufacturer. It may seem that such solutions have a more affordable price than other, but as soon as the manufacturer interrupts the production of the technology, and different components in the system need to be replaced, there is a high risk for high switching costs, in order to achieve a working system again. In a worst-case scenario, the switching to another technology can include all smart home related components, as listed in section 3.1. In such a case, the costs are even higher compared to the design and implementation of a smart system for a new house, because there are also costs involved in the disposal of the old technology. On the other side, the most flexible solutions are those who are based on highly adopted standards with WiFi or IP based communication, for instance. The chance for low switching costs are high because it is predicted that most of the basic network infrastructure is expected to be available for the next few decades. In general, it can be said that switching costs can be kept low when through changes, the technology architecture, as presented in the sections 3.2, 3.3 and 3.4, remain unchanged. Thus, the step of choosing which architecture will be deployed in a building is crucial and can decide about the long-term costs of a smart home system. Furthermore, switching costs will be even lower if the technology and standards implemented are supported by more vendors. KNX, ZigBee, or Z-Wave are such examples. In fact, according to (Stojkoska & Trivodaliev, 2017), Z-Wave is backed up by the most manufacturers, mainly due to their interoperability. According to Z-Wave Alliance, over 35 million Z-Wave products have been sold since they began selling in 2005.

5.5. Conclusion

In the research conducted, it was interesting to note that the perception of costs regarding smart home systems if often contradictory and fuzzy defined. Some talk about expensive investments, other promote the idea that smart home systems got cheap enough to be affordable for every class of people. I believe that the true is somewhere in between, as it highly depends on what the consumer is looking for, therefore, the question is closely related to the target group. Furthermore, is important to define what aspects it involves, when one talks about costs: only short term (mostly defined by designing, purchasing and installation), or also the long-term costs defined through maintenance, flexibility and energy consumption? Regarding energy saving, we cannot say yet that smart homes are usable because of the promised costs saving through load shifting; The infrastructure in most of the European countries is not equipped accordingly. Yet, we can conclude that consumption costs of smart home systems are not unreasonably high, thus researcher should rather focus on energy management (HEMS) solutions, as there is much more potential for energy saving. The maintenance of smart home systems, however, is poorly studied and researched at the moment, hence it is difficult to conclude more precise statements. Nevertheless, it can be said that in general more expensive systems offer a better maintenance support along with higher costs for such services. On the other side, low cost systems are not well supported by corporations, hence targeting technical enthusiasts which can make use of online platforms and open based technologies. Finally, the maintenance costs are not only influenced by the investment costs of the systems, but also by its complexity. In terms of switching costs, the crucial point is to choose architectures and platforms well adopted on the market nowadays, thus assuring that the technologies will be available for the next decades. Otherwise long-term costs can be a burdening factor for the owner of smart home, with less known technologies.

6. ENVIRONMENT – DIRECT & INDIRECT IMPACT OF SMART HOME SYSTEMS Even if smart homes are known for the extra comfort experience and the simplicity they offer to the user, they are also often promised to be important keys in achieving the most possible energy savings in private homes. If such saving reflects to the real-world scenarios, then we can talk about positive impacts of smart home systems on the environment. Further, according to (Pérez-Lombard et al., 2008) the energy consumption of buildings in developed countries, both in residential and commercial domain reaches between 20% and 40%. Based on this, one can easily conclude that if this consume can be lowered, a big impact on the carbon footprint will be achieved. However, sometimes, the requirements for comfort and ecological restrictions may be contradictory (Saito & Menga, 2015). The next sub-points will talk about such impact on the environment, the issues such systems face in the real world and whether there are still potential improvements which can be achieved in in the future. In the contemporary era, smart home applications are being used widely in human’s daily life. Many studies have revealed that smart homes have advantages; however, other research studies have proposed that smart homes don’t have any useful outcomes for the environment. In this chapter, aimed energy savings through deploying of smart home systems are presented at the beginning and then, possible short comes and other related issues are mentioned in the second section.

6.1. Aimed energy savings through deploying of smart home systems

One of the most common subjects in the field of energy savings for smart homes is Home energy management system (HEMS). It plays an important role in improving the efficiency, economics, reliability, and energy conservation for distribution systems (Zhou et al., 2016). In other words, it provides an opportunity for economic incentives of smart home to control the demand-side resources by shifting their electricity usage during peak-load periods in response to the changes in electricity prices. Therefore, smart HEMS is considered as the best system providing energy management services in order to efficiently monitor electricity generation, storage, and consumption in smart homes (Han et al., 2011). Moreover, HEMS Also provides not only the most efficient utilization status of home appliances, but also energy storage and management services for distributed energy resources (DERs) (Son & Moon, 2010). In recent years, the popularity of HEMS has been increased due to high accessibility, convenience and affordability via smart phone and tablet connectivity. Meanwhile, the development of modernized smart grid infrastructures with a variety of two-way communication, metering and monitoring devices lays a solid foundation for smart HEMS application (Lee et al., 2011). In the near future, the extensive use of HEMS will thoroughly change the way of electricity usage and renewable energy utilization in the residential homes. Furthermore, the home scheduling strategies for smart appliances, renewable energy and HESS have been investigated and analyzed to reduce the residential electricity cost and improve energy utilization from electric power utilities. As a result, developing the smart HEMS has become a global priority to support the trend towards a more sustainable and reliable green energy supply for smart grids (Zhou et al., 2016). In the last years (or even months) a lot research have been done on this topic, and (Yu et al., 2019), (Khan et al., 2019), (Lutui et al., 2018) and (Khan et al., 2019) are just a few mentions of relevant papers dealing with this aspect. This work focuses however just on some of them, which brought to light some of the less expected results and insights. In search for market-based energy efficiency investment in households one study has been conducted by (Aboltins & Blumberga, 2018). Based on this study, interesting unpredicted data was achieved. They have shown that increase of electricity consumption led changes in behavior of energy end users, which can possibly be explained by complexity of smart home solutions. In that case, increase of comfort conditions played significant role in the results and data analysis. Although energy saving was a dominant factor in favor of choosing smart home solution, comfort tended to replace savings as the main value proposition. This pilot study served as an initial marker for further deliberation about how to achieve market-based mass deployment of smart technological solutions that were presumed to carry the value of saving energy and reducing cost of energy for the end-consumer. One of the other subjects in the field on energy saving is the internet of things (IoT) which is considered as a conceptual grouping of technological capabilities that enable the interconnectivity of useful devices

41 and also environmental control of useful experiences (Lutui et al., 2018). The IoT services are increased, by providing the consumer simple access to both locally and remote control of fundamental service requirements in the smart homes. Environments are therefore populated by sensors, controllers, and other objects, which are principally controlled with the help of electricity. An overview on this modern technology is chapter 3.4. What is important to remark here, is the consumption that these devices produce, because most of these sensors have to be constantly powered on to deliver data periodically or as soon as these get a request from a central station. Consequently, the growth of the IoT impacts the requirement for renewable energy and energy consumption efficiencies. Therefore, the optimization strategies are conducted by many groups all over the world. One representable example is the Zigbee approach, where the energy consumption is held very low in comparison to standard WiFi solutions (see power consumption in section 5.2). So, clean renewable energy resources with the optimization of a reduced energy footprint by design is the ideal Human Computer Interface to decrease the required energy of the smart home. The optimization of energy requirements has four different components, including life-cycle management, behavioral modification, standardization and simplicity in design. But maybe one of the most impactful optimizations is the behavioral modification. In fact, the Intergovernmental Panel on Climate Change (IPPC) showed that behavioral changes could improve energy savings just in lighting by up to 70% (Lobaccaro et al., 2016). More discussion on the subject regarding impacts on systems through behavior can be found in section 5.2.a.), ‘Reducing Energy Costs’. Based on the four optimization strategies enumerated above, (Lutui et al., 2018) proposed a new strategy for optimizing energy requirements in a smart house through device efficiency. This method emphasized the necessity of balancing the resource requirements for the IOT infrastructure, human experience, and the environmental costs. In smart homes, the energy domain plays the same role that energy prosumer, and each prosumer aims to make their home more energy-efficient and cost-efficient sustainable homes. The acquired energy from self-production can be sold on energy markets or energy domains in the vicinity for the advantages. Currently, most energy-transaction systems operate as counter trade, with the conventional power- generation company being the central ledger. This energy-trading system is less cost-efficient, since energy at singular, fixed rates is provided to homeowners. Peer-to-peer (P2P) trade can be an option between prosumers, but issues of trust, security and efficiency regarding P2P exchange remain unsolved in the current energy market. Another possible solution is blockchain-based energy-trading system that would promote the creation and maintenance of an ecosystem by offering environmental and economic benefits for consumers and prosumers who engage in energy transactions, as proposed by (Park et al., 2018). Its considerable that this technique provides long-term incentives to users while working on a secure and decentralized structure, thereby obtaining a sustainable ecosystem for P2P energy-trade between energy prosumers and consumers. This technique fixes conditions to make every future energy transaction more cost-efficient. By utilizing the blockchain-based P2P energy-transaction platform in the energy trade process, multiple energy resources and home appliances will be democratically connected to provide users with high-quality, low-cost energy at all times and locations. This will increase user convenience and smart home sustainability while minimizing human intervention. The architecture of a next-generation smart home is presented by one of the new research teams, which they considered a new case study as a smart space (Jaouhari et al., 2019). It encompassed various types of services in order to provide a better quality of life for the occupants, named healthcare and energy management. The two different services were implemented, deployed and challenged at a laboratory scale environment, but with real-world systems. Furthermore, a user-friendly interface was provided so the user could have a clear visualization of the various data (i.e., health and energy) collected from all over the smart home, together with alert systems in case of detection of an abnormality in the smart home or other related issues. One of the main objectives of such architecture was to link the smart home to the external service providers, such as the energy utility, in order to first improve these services (i.e., to have a cost efficient-energy consumption) and second, to take a step forward and lead to the world of the smart city. From this work, several perspectives and challenges were identified to obtain the vision of the next generation of smart home, where the occupant can achieve advanced, secure, privacy respectful and easy to use services in the smart home. A first interesting perspective, related to the previously mentioned healthcare services, was to measure the total energy expenditure (TEE). It provided an objective index to track the motion profile of individuals and allows comparing the level of physical activity with the recommendations provided by the healthcare authorities. Wearable technology has attained considerable

42 development particularly, a combination of accelerometers and heart rate monitors has been shown to provide an accurate estimation of energy expenditure. Furthermore, since, one of the objectives of the work was to test the possibility of having multiple services in the smart home, a second perspective was to investigate the challenges of integrating the other services such as the management of the security and safety and the management of the entertainment devices in the smart home. In the research of this paper, the authors also found out a lack of the current research regarding HEMS, which in turn they tried to improve and is worth mentioning here. Firstly, it is stated that “most of the designed infrastructures are based on local area networks where interoperability of various devices with different communication technologies cannot be supported” and second “the majority of the developed architectures cannot interpret and process the sensed and measured information from different nodes at home.” The lack of such standards can greatly impact the efficiency of HEMS as they are not able to fully use all available sensing data in a home. Consequently, they propose a system which should overcome these limitations, however this is just at the prototype level and such a fully tested & functional product is not available yet.

6.2. Short comes and issues

Many years ago, technological advancements were considered minor issue for dreams and future goals like the invention of the wheel, the telephone, the dial-up modem and other breakthroughs. These developments changed the world and how we interact with it. But the most important issue is how do innovations from technology affect the economy and society in human’s life. A quick review of previous patents issued over the past years shows that not only do technological advancements have a positive impact on the economy, but also, they actually expand it. Thus, the new technologies pushed industries to produce more, actually growing the economy and improving the country’s financial health. But at the same time, technology is very much related to environment, with the overlap area between technology and environment becoming larger and larger as show in Fig. 18.

Fig. 18: Mature components of the Earth (Saito & Menga, 2015) This is because new products supported by new technologies require much energy for production and raw materials as input, which mainly come from nature. If economic development continues along this path, the Earth’s natural resources may be exhausted (Saito & Menga, 2015). Even if we can see international efforts to reduce pollution, still it has been very difficult to find sustainable solutions to our environmental problem. It’s clear that more convenient life is one of the results of new technologies and smart systems; however, the way that they are implemented should be considered for the future purposes. Humans’ intelligence may have produced different modern technologies to make lives more convenient, but this is not necessarily good for the ecological requirements of the Earth. We need to consider how to use our intelligence for the betterment of both the future of the Earth and the future of human beings. The balance between technology and ecology should be deeply considered for human beings to be smarter than in the past. One of the common issues in the field of smart home systems is the balance between long term adjustments and adaption to short impacts on human’s life or their unpredictable behavior. This challenges

43 were for instance addressed by (Jose & Malekian, 2015), (Davidoff et al., 2006), (Gazzawe & Lock, 2019) or (Kavousian et al., 2015) and some elaboration in this thesis was also done in section 5.2.a.). This is especially the case when one’s home is equipped with an energy management which deploys scheduling and forecast techniques for energy saving. Another challenge worth mentioning is the customization. Even if, in theory any possible change and adaption to the customer needs is possible, this will firstly increase the implementation cost considerably and second, it will impact automatization routines which work best with preset parameters. Furthermore, learning and accommodation by user may be another issue in some of smart homes because, there may be some learning curve for non-tech savvy people. Also, reliability of smart homes is dependent on the internet connection and electricity. (Gerossier et al., 2018) proposes for instance forecasting algorithms which are robust in normal cases, but they perform poorly as soon as one input parameter like temperature is missing. One research study has investigated the impact of home automation on electricity consumption, related to CO2 emissions and costs (Louis et al., 2015). In this research, five inhabitant types and four different technology deployment levels were simulated. Simulations were run for 1-5 inhabitants and the number of appliances as well as the surface area of the house varied with the number of inhabitants. The study considered eight electricity contracts split into three categories including fixed price, time of use contract, and real time pricing system. Finally, hourly CO2 emission levels were calculated based on the fuel used for electricity generation. The simulations indicated that integrating a large number of smart plugs was counter-productive in terms of energy and cost savings, as their electricity consumption and related impacts offset the benefits achieved by them. Only in case of households with four or more inhabitants did result in a 2 % positive impact. Therefore, efforts should be made on the development of energy efficient HEMS, which for instance are intended for different use cases and needs, to uncover the true benefit. This is given because a general-purpose system often cannot fit all sizes and requests. Furthermore, when talking lowering the carbon footprint it is also important to consider two decisive aspects, on one side the direct energy consumptions smart devices themselves cause and on the other side the raw material needed for the manufacturing and deployment of them. Based on the research done, I concluded that these facts are often neglected, especially for the latter one. There are only few technologies, that offer out of the box very low energy consumptions and have a hardware designed with an ecofriendly principle in mind (see 3.4 for examples regarding low powered devices). However, one has to admit that not all issues are simple to be tackled or completely eliminated. Based on the research and the case studies I was involved in, I identified four such factors which move in the opposite direction of eco-friendliness: 1. More smart devices will consume more current. ➢ This can be partially solved, by making use of such devices that work on very low power (often not the case yet). Thus, more energy can be saved, so that the energy savings offered by these technologies, will not be nulled by the device consumption itself. The best example I found regarding this issue (also mentioned in section 5.2.b.), is the EnOcean technology, where the external energy consumption is nearly zero because it is mainly aimed at energy harvesting from its environment (Withanage et al., 2014). However, this comes at a cost, as this is not an IoT approach, but it depends on a proletary Fieldbus approach coordinated by the company EnOcean itself. This leads to interoperability issues, as discussed in Chapter 7. 2. More information (from sensors) will need to be managed and stored, so database servers need to be constantly available (devices which most of the time are fully functional PCs). ➢ Such servers can be reduced to the minimum functionality needed to the data storage, so energy and material savings are achieved. 3. Specific smart home systems (like fieldbus systems) need extra scarce cooper materials for the internal network, that runs by cable. These cables are expensive in production as they request good shielding to prevent interferences. ➢ Different solutions can be considered here, for instance, transferring bus data directly through the powerlines. Another solution would be to deploy inexpensive ethernet cables whereas the bus protocol and fault recognition is more robust to avoid possible data loses.

4. Smart homes have in most cases the load endpoints (lights, sockets, motors, etc.), separately wired to the distribution cabinet. This in turn means that more copper is needed for powerlines. ➢ One approach to save copper is to group more loads together, on only one main powerline and to achieve separate control for every load by deploying flush mounted actuators. I expect that this will change in future trends, as users will begin to request solutions for such issues, when they will get aware of the potential savings, they would achieve by changing to the technologies. This will be given by the fact that the market is changing according to the demand and soon, less efficient technologies will eventually be abandoned by most users.

6.3. Conclusion

With no doubt, human beings need to be more environmentally friendly as a species on earth. Going green and using sustainable items is necessary for the environment, and it can help people to ensure the longevity of the planet. People care more and more about the environment and if they are correctly triggered, they will play their prominent role to make things better for the environment. Smart homes are the newest frontier for green living. Over the last few years, many people have equated smart homes with technological sophistication and comfort. However, few people considered them as an avenue for promoting environmentalism. As discussed in above parts, considering some of the different smart home products, they could help human to know about all the advantages and disadvantages from an environmental point of view. Nowadays, people can control many of their household operations with a simple touch of a button, a fact that has positively affected the lives of people, both socially and economically. In particular, less time wastage in controls means more time can be saved for other productive activities, which in turn can potentially increase productivity and raise the living standards of homeowners which is one way to have positive effects on the environment. In a nutshell, smart homes can help human beings to positively impact the environment by promoting eco friendliness but still, human behavior must be adapted to benefit from this new technology. Customers should be aware of the efficient behaviors that can be practiced during the day life and they need to be well prepared for this new form of technology, however it is not enough to have systems which inform the consumer about his eco-expensive habits. Eventually we also have to aspire for a new generation of people which will grow and accommodate to new concepts and get used to them from the beginning, so that they can behave in an eco-friendly while being supported by such technologies. Also, new science and technology are changing rapidly and thus, new concepts can be developed where, for instance users can be rewarded in attractive ways so that they get motivated to change their behavior. For instance, if intelligent systems will detect suggestions for energy saving, which in turn will be successfully followed by the user, those may help users to receive discounts for the next electricity bill. Though, it is obvious that such concepts work if and only if there is a good partnership between manufacturers and electricity providers and this must happen in the design and concept phase already. In spite of realizing the potential benefits of smart home technologies, not all technological equipped households are green smart homes. Therefore, it is the role of the relevant stakeholders to ensure that the prices of such energy saving solutions are affordable. Thus, eco-friendly technologies will not be perceived as luxury acquisitions but rather, as economical approaches available for everyman.

7. INTEROPERABILITY – AVAILABLE OPTIONS FOR CROSSLINKING The general definition for interoperability given by the Oxford Dictionary is the ability ‘to operate in conjunction’. Interoperability facilitates collaboration of different applications and devices in smart homes, providing users with improved flexibility in choosing their preferred services. This forms a direct benefit to the consumer and serves as the driving factor towards demand for more applications, services, and content in smart home systems. In simple terms, interoperability between systems allows the communication between two or more machines across different technologies, protocols or platforms, which is also known as the Machine-to-Machine (M2M) functionality. In this way, interoperability affects the effectiveness and efﬁciency of the system, and it enables mutual recognition and continuous data transference between the devices, which ultimately contributes, among other factors, to the usability of a smart home system. Likewise, the analysis by (Shin et al., 2018) has also brought to light that interoperability plays a critical role in the usability and thus decision making when purchasing new smart home technologies. However, an important concern for all the components of a smart home system in terms of operation is their interoperability and method of control states (Kastner, Neugschwandtner & Kögler, 2005). This aspect is seen by many researchers as a stumbling stone, because in general most vendors are focusing on their proprietary platforms. Thus, if consumers need to extend a system, they have either to purchase from the same product line -if the regarded solution is provided- or they must accept the limitation and deploy an isolated system for this new feature they are looking for. (Aschendorf, 2014) talks comprehensively about this aspect in his book. As stated by (Jaouhari et al., 2019), besides the lack of enough interoperable system solutions on the market, even at the a research level, most of the HEMS are lacking interoperability because of the different communication technologies, which hinders the bidirectional communication. For the past two decades, smart home systems could not communicate with each other since they were ‘self-contained’. As technology advances, smart home will get a sophisticated infrastructure and several systems will require sharing of similar physical media. In consonance with (Stojkoska & Trivodaliev, 2017), most developers have been developing the smart home systems in isolation; and this is one major reason why such systems do not integrate or communicate well with other systems. Just as (Saito & Menga, 2015) stated, more focus and emphasis are being put to ensure convergence of the different smart home systems to collaborate. But even if people in academia and industry put an emphasis on this issue, the European project Unify-IoT (Gluhak et al., 2016) concluded that there are more than 300 IoT platforms in the current market, and more to come. All of these platforms base its own IoT infrastructure, proprietary protocols and interfaces, incompatible standards, formats, and semantics which in the end leads to closed ecosystems (Noura et al., 2018). This chapter presents a brief overview over the most known common standards for both, wired and wireless applications. Such standards are in fact attempts to define a common ground for the vendors on the market. However, it will go beyond the scope of this thesis to enumerate and analyze all known standards relevant to such communication strategies. The intent is to present an overview on the state of the art of this subject, in order to emphasize its key role in defining the usability addressed in present work. Secondly, this chapter takes a brief look over the subject of gateways, as these are the communication enablers between different protocols and standards. Lastly, the IP-based approach is presented as a possible solution to overcome the issue of lack for specific gateway solutions.

7.1. Common Standards

Due to technology evolution, scientists, organizations, and unions can now collaborate to attain and push through various standard communication protocols which enables interconnectivity among the software and components and make it feasible for different smart home technology components to work together. Several organizations like IEEE and IEC play an important role in defining standard communication protocols that will support future smart power grids and related smart meters, which are part of the smart home spectrum (Lobaccaro et al., 2016). Some of these standards include IEEE 1901, IEC 61850, IEEE 46

1815, IEC 60870-5-104, IEEE 802, IEC 62056 among others. For instance, ZigBee (see 3.4) is a well- known implementation, specified on the IEEE 802.15.4-Standard. According to (Jaloudi, 2015), data communication is the key to achieving success of connected buildings or homes. Smart devices connected over a network should be able to communicate with each other seamlessly. However, this concept poses a serious challenge to the manufacturers of the different devices because there are not universal communication standards for smart homes. Because of this challenge, businesses and consumers have often found themselves purchasing products from the same brand family, just to play safe. Consumers can be empowered to buy different devices from different product families if better data communication standards are introduced for smart home. Proprietary engineering approach supports creation of several standard solutions to be carried out several times while considering languages and technologies available. Additionally, this approach causes lack of standardized interfaces and requires wheel reinvention. This results in systems that are not flexible both to extend and maintain. However, such challenges can be addressed by evolving a common approach for the engineering and development such systems. This could be achieved by using common set of tools and standards that is independent of the manufacturers. Moreover, the time required, and the complexity of the engineering task will be reduced significantly (Butzin et al., 2014). The lack of universal standards leads to manufactures coming up with products that are based on vendor-defined standards. This make it almost impossible to integrate user interfaces and devices manufactured by different vendors. The next two sections will discuss the different wired and wireless standards available today. a.) Wired There are several standards that are in use today in wired communications. This section will discuss three of these standards including KNX, LonWorks, and OSGi. They were chosen because KNX and LonWorks are seen as proven technology for Europe and USA and offer a very broad product portfolio (Aschendorf, 2014), while OSGi is one of the best known completely open sourced specification on the market. KNX is and open standard (EN 50090, ISO/IEC 14543) that has been designed both for domestic and commercial building automation. As reported by (Richardson, 2015), KNX is an improved version of the three earlier standards: European Installation Bus (EIB), BatiBus, and European Home Systems Protocol (EHS). It can employ the use of IP links, powerline, twisted pair, or Radio Frequency (RF). Networks that operate under this standard makes it possible for devices to form tight interaction and distributed applications. Local Operational Network (LON) works (LonWorks, originally called LonTalk) was designed and developed in 1988 to support control applications (Haden, 2018). It is a peer-to-peer protocol and can run on power wiring, ethernet, or twisted-pair. LonMaker is a configuration tool that is used configure exchange of data in a network by binding the output of one device to the input of another. ANSI has accepted this standard as ANSI/CEA-709.1-B. LonWorks has been accepted in Europe as EN 14908. In 2008, the following standards based on LonWorks were issued internationally: • Communications protocol (ISO/IEC 14908-1) • Twisted pair signaling technology (ISO/IEC 14908-2) • Powerline signaling technology (ISO/IEC 14908-3) • IP compatibility (ISO/IEC 14908-4) OSGi stands for Open Service Gateway Initiative and as the name suggests, it is an open standard and platform for a service-oriented component model (Wu et al., 2007). The platform was founded in March 1999 (Saito & Menga, 2015) and is open both in terms of free of charge use and the possibility for customization. The community of developers, researchers and companies supporting this initiative is constantly growing, so it is expected that this framework will have a stable future as it is considered to be the leading architecture in the domain of research-oriented smart homes (Leitner & Harper, 2015). One specific OSGi based implementation is for instance the OpenHAB project which is a universal integration platform for all things around home automation (Kovac et al., 2015), thus allowing easy interoperability with different other systems (Lobaccaro et al., 2016). This project is also suggested in section 8.4 as one of the most common used open source platform thanks to these characteristics.

47 b.) Wireless According to a review by (Parikh et al., 2010), there are several wireless communication protocols available today, each with its opportunities and challenges. This section will only briefly present five of them. Zigbee - is a wireless protocol that has been designed to work on mesh network, where one device is used to distribute signal to other devices thus expanding and strengthening the network. Zigbee is also discussed in section 3.4. Z-wave - is an open source protocol, and like Zigbee it is designed to work on mesh network. (Schatz, 2018) distinguishes the two standards based on speed and energy consumption as follows; Zigbee is six times faster than Z-Wave but consumes more energy to cover the same range as Z-Wave. Infrared - is one of the simplest protocols which provides one-way communication. It is mostly implemented in remote controls. However, this protocol was criticized by many as it could be manipulated by an intruder that has knowledge of the correct IR code (Jiang et al., 2004). Bluetooth - is a short-range wireless protocol based on the IEEE 802.15.1 standard (Pothuganti & Chitneni, 2014). It covers in most configurations 10 meters and is often used in headphones, phones, and speakers. The system detects existing signals by employing its adaptive frequency hopping just like Wi-Fi and minimizes interference by negotiating a channel map. c.) Interoperability beyond the protocols Common standard does not only entail the various communication protocols and approaches, but it also includes models that can be adopted to achieve interoperability. To better understand and have a deeper insight on the concept of interoperability, we can break it down by classifying it. Heterogeneity has made it possible to view of interoperability issues in smart home system from different perspectives. Heterogeneity is a concept that has been around since the beginning of time and we can relate it even in our daily lives, for instance, people talk different languages. This concept can also be applied in smart home where there are different elements that make up a smart home system such as communication, devices, applications, services among others which are required to collaborate effectively to offer the desired services to the consumers. (Heidemann, 2013) states for instance that the communication within one system can be compared to a language. I order for components and devices to communicate with this system, they must speak and understand the same language. Two models have been proposed by (Tolk, 2004) and (Pantsar-Syväniemi et al., 2012). These models are based on a six level structure; Tolk’s model is made up of six layers that describes interoperability based on: (1) data exchange: he referred this layer as syntactical; (2) no connection: it describes the missing of physical connections means among systems; (3) technical; it describes the basic network connectivity; (5) dynamic and pragmatic: it elaborates the applicability of information; (6) conceptual; this gives the world perception. Pantsar-Syväniemi et al. suggest a similar model that is also made up of six levels namely communication, connection, behavioral, dynamic, semantic, and conceptual. Inspired by these two models mentioned above (Noura et al., 2018) describes the different perspectives on smart home interoperability including (1) syntactic, (2) device, (3) networking, (4) platform, and (5) semantic interoperability (see Fig. 19).

Fig. 19: Perspectives on interoperability by (Noura et al., 2018)

The breaking down of interoperability in such concepts, makes it possible to narrow down and provide the most ideal interoperability solutions and strategies that can be implemented to achieve the full potential of smart home ecosystems. By looking at the diagram above, the interoperability concept can further be broken down to elements and thus a smart home system is made up of several devices that have different capabilities and operate on dissimilar protocols. The next two sections present two ways to overcome possible interoperability issues.

7.2. Gateways

In the domestic section of automation, one of the first suggestion to overcome interoperability issues was the Home Gateway, as presented by (Saito et al., 2000). On this basis and architecture, different research and implementations were conducted. The OSGi framework was for instance deployed on such a gateway. The most common approaches are embedded control gateway and simple gateway. Both approaches offer consolidated connection by collecting data from several end points (Hourdouillie & Pollock, 2016). It is important to point out that a gateway is not similar to a router. A gateway acts as a bridge and connects different communication interfaces with different types of data while a router connects devices sharing similar interfaces and similar traffic. A sample system interconnected through gateways with different technologies is presented in Fig. 20.

Fig. 20: Integration of bus-systems into a decentral bus-system (here KNX) (Aschendorf, 2014) This approaches relay on gateways which are working on the fieldbus level. The slightly newer approach is to move away from the different technologies toward the general and well-known internet network. More recently (Baló & Alexandru, 2017) suggests a communication protocol which can be implemented in gateways, to move away from the hard-coded command-response static approach. Such gateways would than facilitate IoT communication with multiple interfaces by dynamically adapting the communication to the peers in the network, as each of them would share in the initiation phase, the supported parameter set. Regarding the market availability, (Papcun et al., 2019) points out one of the commonly used gateways as TM4C129x IoT gateway MCU. It is based on a 120MHz to enable the processor to handle many-to-many processes. The gateway offers an environment to preprocess the data locally before transmitting it to the cloud. This helps in minimizing the volume of data that needs to be sent to the cloud thus increasing the response time and reducing network transmission costs.

7.3. IP-based approaches

To move away from the dependency of different technologies available on the market, the emerging trend is to make use of the well-known Full TCP/IP stack to achieve a more general connectivity. This enables the actuators and sensors to connect directly to the IP network and enable point-to-point communication between the IP network and the sensor network. One major benefit of using this approach is that protocol translations and gateways are not needed. Additionally, this approach does not have limitations like those of gateway-based approaches. Fig. 21 show how this principle works.

Fig. 21: IP based interoperability (Noura et al., 2018) This approach suggests so that the only bridge that every technology has to offer, is an IP-Gateway, thus reducing the multitude of gateways to support several protocols. However, as HTTP is not designed specifically for M2M communication it introduces substantial protocol overhead. However, from the performance perspective, this should not be an issue, as sensor networks are generally slower than IP networks. A successful implementation of this approach is for instance the IP-Symon project. (Aschendorf, 2014) shows in Fig. 22 an incomplete list of the multitude of systems that can be interconnected through this software. In addition, IP-Symcon also provides a Web interface that facilitates the monitoring sensor values and the control the actuators.

Fig. 22: IP-Symcon as a software gateway (incomplete listing) (Aschendorf, 2014)

7.4. Conclusion

There are many platforms and many protocols, but it is hard to convince the market to go in only one direction, and this is mostly caused by (1) competitive concerns and (2) lack of predefined standards and common models from the beginnings (Bregman & Korman, 2009). Thus, there are a few solutions on the market and a few gateways which can bridge systems. But based on the conducted market review, even those few solutions are expensive and not very versatile. Interoperability will enable collaboration of applications and devices and offer end users greater flexibility in choosing the services they desire. These aspects including different solutions and approaches, have been presented in this chapter and the case studies have proven that they are able to overcome this issue. Nevertheless, the solutions are mostly just at a proof of concept level and the market has to catch up with these solutions and ideas. In my opinion, the most promising approach for the future is to move away from platform-dependent interoperability implementations, to a general model, for instance the IP-based approach, as suggested in the last part of this chapter. This will offer the ability to be easily extended in the future, without being forced to adapt, change or purchase new hardware, as it is the case with platform specific gateways.

8. OPEN SOURCE – INDUSTRY OPENNESS ON SMART HOME SYSTEMS In the modern world, technology has made access to information possible, whereas opposed to some recent years ago, it is possible to access information services enablers easily. These enablers include software and hardware, where some of them can be accessed and be used freely. This brings to the understanding of Open Source (OS) software where the software can be readily available, including its source code, where any interested user can freely use it, edit the source code, and distribute it without having to request permission from anybody (Monacchi et al., 2013). Open source software is maintained by the Open Source Initiative (OSI), that enhances free redistribution and unrestricted access, providing free scope for use and at the same time ensuring technology neutrality.

8.1. Open source licenses

Despite the open source products being free, they still need to be licensed. According to (Lerner & Tirole, 2002), open source software needs to be licensed to provide developers with copyright protection for their original works. In such cases, instead of selling these works they are copyrighted. Licensed software also allows developers to have the full liability of their works especially when the products are not working as required and also when they need to restrict users to share the software on other machines. Licenses on the open source software also ensure that their uses are well governed. Likewise, (Rosen, 2004) comprehensively describes the OS licensing in the light of Intellectual Property Law. The book explains that intellectual property is a rule that recognizes and protects independent works of individuals. In this case, Rosen sensitizes the important of protecting the works of open source software. The book is important as it provides insights into the effects of using different licenses on a product, where this might result in conflicts on who is the rightful owner of the software. Furthermore, it provides information about the most common types of open source licenses, some of which are also mentioned in this work. The open source licenses are offered by the OSI, that have a list of more than sixty different licenses, but only a few of them are used in most cases. The IEEE must also verify the licenses offered by the OSI, and in this case, the open source licenses to be studied include the GPL v3, Apache, MIT and CC BY-SA 4.0 licenses. GPL v3 is a type of open source public license that enables users to freely run, modify study and share a piece of software. These licenses provide the basic freedoms of use, and most importantly, free here doesn’t apply to price but rather to the freedom to distribute, alter the source code if need be and also study it (Crowston et al., 2012). The developers must not deny any users of rights to use the open source software by revoking the license after some time of use. The GNU GPL ensures it protects the rights of users by asserting the copyright on the software and also providing legal permission to make copies, share and alter the software. The GPL license, however, does not provide a warranty for the open source products (Withanage et al., 2014). The other open source license that has been approved by the IEEE is the Apache License. It provides freedom of use of software with no restrictions as seen in the BSD license. However, it puts more stress on legal issues in handling more ambiguities in and makes simpler licenses to be able to create more patentable software. This prompted the Apache foundation to write licenses that had an explicit patent license known as the Contributor's License Agreement (CLA) that was more seamless and consistent (Monacchi et al., 2013). Next is the MIT license, also known as the Massachusetts Institute of Technology License. It provides end users with software rights of modifying, copying, sharing and merging. It does not allow advertising or the use of the name of the copyright owner for promotions (AlMarzouq et al., 2005). This license is more flexible as compared to GPL as it enables rights for broad distribution and copying and exclusively providing developers with rights to modify the products the way they may wish.

Lastly is the CC BY-SA 4.0 license also known as the Creative Commons Attribution-Share Alike license. It is a type of copyleft license that allows free cultural works and provides four different kinds of freedoms that include the following; 1) Freedom to use and perform work that allows for use in both private and public purposes with no exceptions either in the form of religious or political considerations. 2) Freedom of study and application of information provided by the license, which means that users are free to use the knowledge gained from the licensed works freely with no restrictions. 3) Freedom of the redistribution of copies, including selling or swapping them for free, irrespective of whether the user uses them independently or as a collection of users. No limit of the amount of information that can be copied or redistributed (Steiniger & Hunter, 2012). 4) Freedom of redistribution of derivative works, where this is an opportunity provided to users to have the ability to improve the works of the product, with no limitations whatsoever to modify or distribute any version of the product or works improved from the original version (AlMarzouq et al., 2005). The only restrictions in this license are that there should be not any restricted access to the works of the product including technical measures or try to limit any of the freedoms mentioned above. Also, the authors must be allowed to retain the license notice. For derivative works, they must be produced under an identical license as the original work.

8.2. Can Open Source Smart Homes be completely free?

Because smart home systems are a combination of software and hardware, in this section, the question will be answered concerning to both aspects. a.) Software The software can be completely free, depending on various possibilities. Open source software means free software, but different issues define free programs and hold different values. Free software must take into consideration of user’s freedom to be able to run, alter, study and distribute it either with or without performing changes (Withanage et al., 2014). These freedoms are the most important aspects when it comes to an open source software not only to the individual but also to the society as a whole as they play significant roles in ensuring solidarity in social perspectives, especially through sharing and cooperation. Another important aspect of open source software is that they enable society to take significant steps towards digitalization. Is especially visible in the enhancement of digital sounds, words, and images, and thus bringing the true sense of freedom. This is true because millions of people today see the essence of digitization through the use of open source software. On the other hand, non-free software could bring a lot of social problems as not everybody can access them, hence bringing inequality in the social level, and this can be very detrimental in this era of the digital age (Stojkoska & Trivodaliev, 2017). In conclusion, yes, the software can be completely free. There are some well-known open source software solutions for smart homes and some of them are briefly presented in section 8.4. b.) Hardware Open source hardware, as explained above include specification of designs of different objects of which these designs must be licensed, giving permissions to be edited, modified, created and be distributed by any user. As opposed to open source software, open source hardware incorporates some legal practices that do not refer to a specific type of product or object. It can be in the form of logic designs CAD drawings, blueprints or schematics (Monacchi et al., 2013). Thus, being open source, users are given access to these tools where they can have access to edit or read the underlying characteristics that define a physical object. Some of these hardware parts are mentioned in section 3.1. While open source hardware licenses can be free, it cannot be free in terms of zero costs of the final hardware. This is because, after the design, implementation of the design into a final physical product requires an input of materials and cost of production (Stojkoska & Trivodaliev, 2017). However, the cost of the final product can be minimized because the cost of the conception phase is not included in the end product. This is however opposed to the cost of the product were everything to be done from scratch. So, one cannot assume that hardware products are already present, just because of the available open- sourced knowledge. Following three factors plays here an indispensable role:

- Knowledge or know-how: it is needed to understand the open information and so to be able to transform it into a physical object. - Raw materials and the tools to transform them into the desired product. - Time expenses. Even if this phenomenon of open sourced hardware is hardly present, there are however concepts where the idea of open source hardware is followed. These initiatives enable the consumer the possibility to construct, develop and adapt the hardware by itself. (OpenMotics, 2018) is such an initiative for example. Here, the hardware is open sourced (under CC BY-SA 4.0), which means that the customer/consumer has access to the PCB files (including BOM and schematics) to create, adjust and manufacture his hardware.

8.3. Challenges of Open Source Solutions

In the case of implementing smart home Systems, some challenges are encountered. One of these challenges is that the developers of the smart home systems lack the necessary experience in implementing these applications and hence leading to impending failures. Open source solutions may not be the best option in applying the freely provided knowledge to solve Home Solutions problems. There is also costs in time used while implementing open source solutions (Withanage et al., 2014). This is because developers may invest a lot of time implementing freely available information which in turn may not lead to operable artifacts as fast as compared with other smart home solutions on the market. Relying on such solutions can be an implication that the developers or enthusiasts do not have the necessary know-how and are unable to apply the best practices in coming up with unique and state of the art smart home solutions. Carrying out maintenance and troubleshooting of applications based on OS solutions can also be a major drawback, when deploying open source smart homes systems. There can be also a problem in trying to locate and troubleshoot problems as it may not possible to reach out to the original developer or the designer (Zhou et al., 2013). Since one cannot easily find specific solutions on the internet or within the online supporting community, this may force the users to seek external support to solve the problems, an activity that can lead to increased costs for maintenance and future upgrading. Some of the solutions to such challenges include having a well-abled team that has deep interdisciplinary knowledge in electronics and electro techniques, mechatronics and both high level and low-level programming languages. This is important in the sense that the technicians should not only rely on the solutions provided by the open source products but also have their knowledge and experiences to do their original works and further innovations in designing and implementations of high quality and state of the art smart home system solutions. But not only the developer is requested to have such hard skills; based on the fact that open source solutions tend to be less automated or user friendly (because of the lack of resources) one user has to be more prepared to accomplished more manual tasks or to self-troubleshoot different breakdowns of the system.

8.4. Availability of open-sourced Smart Home Systems

Various open sourced SmartHome Systems can be deployed freely at least regarding the software aspect of these solutions. Next points briefly enumerate some of the most common smart home systems that include the following: HomeAssistant This is an open source home automation platform that can be used in various computer systems that use Python 3 Raspberry Pi and various Network Attached Storage Devices. The technology has been greatly applied in shipping, specifically on docker container and other areas that need to control hardware from locks to lights. MisterHouse The technology uses Perl scripts to monitor devices that can be remote controlled, where it can be controlled using voice, time, weather, lights, etc. it is appropriate to alert users in specific times such as

53 answering calls or waking them up. MisterHouse is Open Source and uses GPLZv2 license and is readily available at GitHub. OpenHAB Another open source home system is called OpenHAB. It is one of the most common and preferred solutions as it supports various devices that most members of the community can afford. It is deployed on any device that can run a Java virtual machine (Lobaccaro et al., 2016) and it also supports different communication integrations to allow controlling by IOS and Android devices. At the same time, it facilitates the creation of customized user interfaces for home systems (Withanage et al., 2014). OpenMotics This system is open sourced, from both perspectives, so it has as well hardware as also software published with open source licenses. This solution provides control of various devices especially by offering hardwired solutions. Its source code is licensed under GPLv2 and readily available for download at GitHub. Domoticz The home automation system supports various library of devices such as smoke detectors, remote controls and weather stations, where it can also be integrated into various weather websites. It is easily accessible from most of the desktop browsers as it is designed using HTML5 in the user interface and can run in low powered devices such as the Raspberry Pi (Putri et al., 2018). Calais This is a full stack home automation system that supports various interfaces including servers, web application and other mobile application including android and IOS. It can also run on Linux OS. It is coded initially using French, but the documentation can be translated to English. It is freely available at GitHub under the GPL license.

8.5. Conclusion

As seen from the above discussion, various high-end smart home systems are available freely, but the major issue with them is that they can lead the users to incur high compatibility (adaptability) costs as most of the open source software is not customized. It is also well known that although some home security systems are open source, free and provide most solutions and concepts online, the ideas sometimes may require a lot effort to implement and at the same time fail to meet customers’ needs, and hence more costs (mostly time related) incurred during customization of the product. Despite this, it is true that the open source approach of smart homes has increased the accessibility and usability of home automation solutions, even if it is not for the use case for every targeted group of customers. For instance (Sas & Neustaedter, 2017) presents interviews with 18 participants from two green communities who built and used an open source DIY energy monitor, with the aim to explore the end users DIY practices of making such complex electronic devices. The findings encouraged the designing of transparent open hardware technologies. In fact, one can easily see OS concepts at work, when looking at present implementations, such as Kovac’s one. (Kovac et al., 2015) proposes a solution which is running on a Raspberry Pi device with the support of the OpenHAB platform, that can monitor system resources and network activity of different network nodes. This further shows that open source applications prove to be suitable in interconnecting other applications via the network, and hence organizations can easily extend their systems to serve more customers (see also Chapter 7). So yes, smart homes systems can be open source based, and there are a few working examples on the market and in the research field. But beyond the OS concept, the most used and well-known deployed solutions (yet) are costly and closed source technologies, which are using proprietary approaches, that cannot be adapted very easily to every customer need. Thus, they have to stick to the predefined sets of customizations the vendor/manufacturer is providing out of the box (Lin, 2013).

But maybe the biggest hindering point in seeing open source approaches as the crucial factor which increases the usability of home automation systems is that such solutions can only be set up and deployed by technically skilled personas. This is because of the nature of such systems, as they do not work in a plug-and-play fashion and are not stand-alone artifacts, which can be installed and set up in some predefined steps that everyone can do, just by following some simple instructions. This is not possible for the reason that, as mentioned in the chapters before, with the given state of the art, smart homes systems consist of several components and technologies that need to be combined through different interfaces and hardware. Based on these conclusions, one can easily see that open source projects in this area have to go on step further and offer solutions that go beyond just software solutions, to achieve full functional systems. In light of present research, only one project aims to fill this gap by offering not only software but also hardware which is open sourced. The other systems can be more likely considered as tool-sets, libraries, or skeletons which give the end user a basis, designed to help him create his own customized home automation ecosystem. However, he needs to accomplish at least two main steps beforehand: 1. Having Know-How or otherwise finding the right developer who has the knowledge about both the open source solution and the selected hardware, 2. Find the hardware, whose specification matches with the defined task or function and 3. Make sure that the hardware supports the same protocols as the chosen open source software.

9. SECURITY – IMPACT ON PRIVACY AND HOME SECURITY One of the objectives of deploying smart home systems is to achieve more security in one’s home. For instance, (Gazzawe & Lock, 2019) is one of the authors who states this. This aspect was even one of the visions for the first smart home pioneers. However, it was surprising for me to find out that this section is nearly neglected or not tackled enough by companies who offer smart home systems. In their enthusiasm to develop new solutions and functionalities, privacy and cybersecurity are often forgotten (Nyborg & Røpke, 2011). For instance, during the interviews conducted for this thesis, (see 2.2) one interviewer, which is the reseller and implementor of one of the current smart home technologies, witnessed that the cloud solution suggested by the manufacturer they are collaborating with was reported on community platforms (forums) to be easily hackable. So, they decided to implement their own VPN solution to avoid this security flaw. But before moving further towards the discussion about security, the difference between the term safety and security in smart homes must be clarified. In the first sub-point, general findings of security challenges and suggested solutions found in the research and the case studies will be addressed. The following three sections will then discuss privacy, software and hardware hacking and social hacking. The fifth point will tackle a subject not very common in the past but in present times more and more often addressed, namely the phenomenon of the Internet of Toys (IoToys) and the privacy concern related to it. Home safety vs. Smart Home security Home safety refers to the phenomena whereby a house is made secured in terms of any disastrous event such as a robbery, a burst water pipe, a fire, etc. The home is secured by installing different types of sensors all around the house, along with a central system that tends to control and monitor all the sensors, and upon any irregular movement during the absence of the house members, reports to those professional monitoring companies through which the security system is provided. These professionally installed systems can easily get installed through vendors like ADT, Comcast or Vivint. Contrarily, smart home security is defined as the security and privacy of the smart home device or system itself, in isolation. In the following sections, the security or vulnerabilities are checked in the system and seen whether any third party can easily attack the system, or the system is invulnerable to such attacks from any intruder. In fact, smart home technologies should be the digital agents who provide safety through their features. But if those are not protected and secured by themselves, they will rather transform to danger and harm factors, instead of fulfilling their intended purpose.

9.1. Security Challenges and Solutions

Due to the significance of private information a home environment pertains to, smart homes need to adopt quite strict security requirements. Described below are the core challenges that exist in an automated home which restricts usage of standard security mechanisms adopted in traditional networks. Table I shows that computer's storage capabilities and computing performance is constrained since the majority of home automation system devices are designed to work with reduced-size hardware and low-power (Lee et al., 2014). Table 5: Specification of smart home devices (Lee et al., 2014)

It is also important to remark the different network protocols. As soon as there are more protocols used, the complexity of security measures increases. Most of the smart home security listed here comes from the decentralized network approach to the smart home systems (see 3.4). The idea behind the decentralized approach is that the sensors are not centrally connected with a controller, rather the sensors tend to own control nodes (one or more) which receive and process the data and then accordingly take a corrective measure against any occurrence of irregularities in the environment through actuators. The security concerns raised by the decentralized approach, according to (Jose & Malekian, 2015) are enlisted below. • A professional attacker owing to have previous knowledge regarding the network and the exact placement of the actuator can easily disconnect the system from the network. For such a case no alert function come into use. • If the attacker tends to have the accurate hardware, then the communication which initially also generated in clear text can easily eavesdrop on it. • A smart home system carries many complex natured works that need to be analyzed and processed at several parts and inputs during different points of time and from different parts of the home. This tends to demand few processing efficiencies, storage and power that a simple actuator node fails to presently deliver. There had been many studies taken place regarding the security of smart home systems, and how the privacy can be maintained. However, the literature review of almost every investigation indicated that while testing for the security of it, only a few components of the system were taken into consideration, or rather few technologies. It was later judged that the integration of them might bring about new security inferences (Mahadewa, 2018). Thus, one can say that in the past, there always lied a gap in the literature with respect to the security analysis of the home automation systems. For instance, regarding HEMS (Jaouhari et al., 2019) mentions that among the studied research works, none of the solutions deal with the security aspect associated to these technologies, even if those are dealing with sensitive information like sensor data which is stored, processed and dispatched to the actuator components and users. The study of (Mahadewa, 2018) analyzed the security of home automation systems by bringing in such a framework, that integrates any single component through end-to-end-application-layer specification from the input smart home. She tested 3 real-world smart home systems. Later on, the extracted information is properly validated in order to identify security errors of the system. A three-layered framework was proposed which resulted in a thorough investigation regarding the vulnerabilities of the systems. She identified 12 flaws in a total of 3 systems in their different components indicative of the fact that there exists several vulnerabilities in smart home systems, which require an adequate testing tool or application for the systems to identify and then later mitigate such weak-ends. A closely related study related to that of Mahadewa’s was done by Ramljak, who thoroughly scrutinized the most efficient open source smart home system, Open Home Automation Bus (see also chapter 8.4) that supported several other IoT devices and acted as a platform for them. Ramljak at first went briefly through OpenHAB designed security and supported features following the challenge of a static source code analysis of several most used OpenHAB packages (called bindings) and carefully crafted test cases that revealed many undocumented features of the platform. Subsequently, he exploited security errors by building two ‘proving-the-concept’ attacks that: (1) OpenHAB system denial of service; (2) inject custom binding for message bus monitoring and control; the study was successful with security’s greatest carry outs for the architecture of custom OpenHAB bindings (Ramljak, 2017). (Perera et al., 2016) argues that this situation is given “partly due to the lack of systematic methods for designing privacy that can guide the software development process in IoT”. Here Perera proposes several securities rules, a protection by-architecture system, used to evaluate security abilities and holes of existing IoT applications just as middleware stages. It is assessed in two exposed source IoT middleware stages, in particular, Eclipse Smart Home and OpenIoT that shows how the system is utilized along these lines. Currently, the Internet of Things gadget safety has turned out to be one of the real worries of the Information Technology Industry. As an answer to this, the blockchain approach emerged. It is believed that it will be able to revolutionize the security aspect of this field by atomizing and decentralizing

57 transactions and mechanisms. Blockchain makes sure that no block or set of data is tampered with as all the blocks are chained, wherein, if the content of any one block is changed, it will affect the code hash of the next blocks and the user will come to know of the unwanted action taken upon it. Since IoT also demands automatic transactions that need to be completed privately and securely, blockchain will be of definite help. All devices communicate in a decentralized fashion using blockchain and do not store all of its data on a central cloud. (Ms. Falguni Jindal, 2018). Gupta and Varshey, by way of such an examination, are utilizing the blockchain method to build up a system for security and the board of information on the web. They built up a structure which indicates how brilliantly gadgets correspond with one another while the blockchain is acting like the spine. The system fills in as an adaptable and vigorous arrangement, so as to address security and identity related worries of the Internet of Things, the proposed structure is additionally contrasted with existing models (Varshney & Gupta, 2018). Another key component in home automation systems is, as already mentioned in the chapters before, the Energy Management. The fundamental capacity of the HEMS is to ideally control the activity of in-home gadgets and machines concerning diverse goals (e.g., limiting vitality costs and boosting solace level). For this purpose, it considers the measures given by keen meters, the data on the activity of the gadgets, clients' solicitations and outside signs, for example, vitality costs and meteorological data. The HEMS can likewise utilize data about the nearness of individuals over a period and construe an inhabitance model of the occupants. This would upgrade the board of the framework inside the planning time frame. Moreover, the inhabitants of the keen home may have concerns about their Security, Privacy, and Safety, which is an essential perspective that needs specific consideration. Right off the bat, since clients are constantly stressed over their security and the one of their family and their having a place, a few arrangements have been proposed so as to react to this need, which are predominantly: savvy observation cameras (i.e., Cisco), shrewd locks (i.e., August), brilliant trackers (i.e., Tile) and keen firewall (i.e., Cujo), to mention a few. Besides, the client's information must be shielded from any outside dangers. Consequently, a few estimates should be considered when building such a system, which are chiefly: the confirmation by checking the clients' personalities, the secrecy and integrity of the information by encoding every one of the trades and with the outsiders (i.e., outer specialist organizations), and last but not least, the entrance control to enable just the approved clients to get to the administrations of the keen home. In such manner, access delegation should also be considered, as outer people or services connecting in the smart home may need access to some essential or basic services inside. As also stated by (Jaouhari et al., 2019), the cooperation with the external provides needs additionally specific consideration since it accompanies its very own difficulties and issues, in the end, the security and protection ones. As shown in Fig. 23, these might include any specialist co-op for the previously mentioned classes, just as correlative administrations.

Fig. 23: Interactions with external PROVIDERS (Jaouhari et al., 2019) 58

9.2. Privacy

We live in a world where almost every task we perform is embedded with technology – from automatically opening garage doors, to making use of a cell phone to control the spins of the washing machine while being away from home. We have been drowned with all the new technology that gets introduced, as we tend to trust its security and privacy terms. Hence, privacy has always been a factor that drives more users if adequately taken care of, because every user wants his privacy to be maintained whatsoever. However, there is a high risk of privacy invasion and damaging consequences thereafter the occurrence, in case if any sensitive information is let out of the system or out of user's hand, without his consent. It is due to the data sensitivity, minute leakage of data, interdependency that could lead to an immensely harmed privacy of the user. Additionally, the acceptance of IoT deployment will only occur if the infrastructure is privacy- preserving, trustworthy and secure. IoT devices, although may help secure and monitor homes, can also become rich sources of forensic evidence. The main issue in an IoT based home is that an attacker can eavesdrop the information transmission between the IoT device and a server, and then alter this information (Krishna & Dharma, 2017). Leaked personal data from IoT can be utilized to create profiles from the inhabitants inside the house, so that the attacker gets an idea of how many persons and which persons are living inside. One can collect information about an individual’s age, gender, preferences and daily routine. By integrating all the data together, an attack in the house can be planned out quite easily. In this context, (Dorai et al., 2018) extensively presents a use case how one can create a life history line, just by using mobile phone backups that stores logs about smart devices sensors and applications within the private facility. In a much serious sense, these features also have proven to be the key answer in recent court cases. An example is a case in which an individual's Fitbit (a smart fitness band) activity was able to contradict the sexual assault allegations, which were originally presented to the court. This was possible through the continuous logging of the device that contained an accelerometer. Thus, the sensor logs confirmed that the persons involved in that case were, in fact, awake, as opposed to the original claim that they were asleep (Do et al., 2018). Since IoT contains heterogeneous systems administration advances and gadgets, for example, radio recurrence recognizable proof (RFID) labels, cell phones, and sensors—it’s challenging to deploy conventional privacy protocols, as high-performing devices sometimes require advanced protocols that are too bulky for these small devices. Nonetheless, lightweight protection arrangements are effectively tractable by ground-breaking attackers. Cisco evaluates that by 2020 there will be in excess of 50 billion Web-empowered gadgets, including iceboxes, TVs, and scales (Porambage, 2016). Internet, cloud specialist co-ops (ISPs and CSPs) and customers have just experienced numerous worldwide security dangers because of the utilization of unavoidable items and administrations. Late press reports feature a few protection infringements in IoT applications. For instance, in June 2013, the press uncovered security dangers identified with the Planning Tool for Resource Integration, Synchronization, and Management (PRISM) program, which the US National Security Agency uses to gather private electronic information having a place with clients of significant Internet administrations including Microsoft Outlook, Google, and Facebook. Further, a yearly Internet security danger report guarantees that portable malware assaults expanded by 58 percent from 2011 to 2012, and 32 percent of those assaults endeavored to take data from the gadget's contact information.5 According to a US Federal Trade Commission (FTC), report on consumer privacy, privacy by design (PbD) is the most prominent approach to overcoming IoT privacy issues. Privacy is the right of individuals or cooperative users to keep up privacy and authority over their data when it's uncovered to another gathering. In IoT applications, security difficulties can be distinguished principally from the viewpoint of purchasers and they are put away datasets. Since both CSPs and ISPs have a client's (client's) individual data, they could out of the blue start protection dangers and assaults. IoT systems can include tens to a great many gadgets with heterogeneous qualities identified with asset limitations, portability, versatility, level of self-sufficiency, interoperability, etc. In this way, protection issues in IoT shift broadly regarding the applications included (Porambage, 2016).

9.3. Hardware & Software Hacking

Security concerns in regard to the Internet of Things have turned into a well-known issue for the individuals who decided on a smart home system living. Most gadgets don't have appropriate information encryption or right confirmation making them vulnerable to Denial of Service (DoS) assaults, man-in-the-center attacks, or different malignant endeavors that bargain a mortgage holder's network, physical security or protection. Programmers, with refined instruments, can break Wi-Fi systems at that exact moment, after which they can without much of a stretch screen traffic of the system. This empowers programmers to see whether individuals are in their homes or not since it is basic for them to screen the traffic examples of a smart home. To condense, IoT can be a route through which the aggressors can screen individuals despite the fact that they don’t get to these keen homes from wherever they are working (i.e. workplaces, lofts) One specific finding for instance that caught my attention, was regarding the Zigbee technology, because as acknowledged in several chapters before, this specific approaches seems to be promising: According to (Yang, Liu & Cui, 2018) the ZLL touchlink commissioning protocol (part of Zigbee protocol) is vulnerable to attack due to lack of identity authentication and network key update mechanism. Yang proposes therefore and security enhancement protocol that incorporates a network key update mechanism. However, such improvements must go a long way until they reach the market and until then, every consumer is exposed to these security flaws. But generally speaking, the basic hardware found in smart home devices can be exploited in some ways presented as follow; For example, Bootup procedures are a good hint to exploit. Another problematic phase is the pairing of devices, where, in order to allow an easy connection, some devices allow any connection in a limited time window. Also, one hacker, as soon as he is aware of the system inside the house, can flood the devices with a dozen of requests and so make them non-responsive anymore. At the same time, the network is overloaded and so, no communication between peers can be deployed anymore. This does not necessarily end up in getting the data or understanding the data from outside, but rather to badly destabilize smart home systems in such a way that basic task like turning lights on off will be not possible anymore. Another attack can be on the power line and the electricity. If one has access on the power lines that lead in the targeted house, he can influence the normal operating of smart devices by manipulating frequencies or introducing wrong flows in the system, which in the end can cause abnormal operation of the devices. It is enough for the attacker if he succeeds in provoking a complete system reboot. After this step, he can exploit the bootup procedures mentioned in the beginning. The risk added by such power line attacks is that even the security frameworks by themselves or other alarm systems will be disturbed which in the end can lead to an unpredictable state of the complete smart home system. A further conclusion, based on my analysis is that once the software and hardware are delivered, there are no further updates, improvements or long term support offered by the delivering company, a fact also confirmed by (Sas & Neustaedter, 2017). The lack of retrospect updates can be compared to the issue of not updating operating systems on personal computers. This is especially critical when wireless solutions are involved, and these systems get outdated. As soon as new backdoors and flaws are discovered these flaws remain in the outdated system available. The fact that most of the companies don't offer to the customer any possibility to manage or to maintain the systems because of proprietary solutions, makes it even more critical because the user is bound to this solution without any possibility to improve the system by himself at least. Finally, another claim can be made here: Exploiting and interfering with the frequencies used by IoT devices in the house can be dangerous. This is because one cannot completely avoid frequencies to leak out of the house and at the same time, he cannot stop the penetration of other frequencies from outside. The attacker can so introduce new information through wireless signals, or he can at least try jamming these wireless channels, in order to prevent normal communication between peers inside the house. Despite the fact that individuals use encryption innovation to ensure security, these advancements can't secure the protection of the sender or beneficiary, particularly as to the correspondence designs (e.g. how frequent, when who, information arrangement and message lengths) present in ordinary system traffic.

Accordingly, these correspondence designs offer helpful data to programmers and are the premise of traffic investigation (Yoshigoe, 2015). Even though there are not many events that took place, supporting the phenomena of hardware and software hacking of Internet of Things. However, the growing awareness regarding the smart home system and the vulnerabilities attached along with it adds all the more reason to anticipate attackers to soon get into the system, intruding someone’s private life. It is vital therefore to at first analyze the risk of a system and how it is susceptible to an attack, and thereby coming up with a solution, which is ethically, legally and socially correct as per the cybersecurity laws. Since the Internet of Things is a new innovative way or rather a paradigm that people are increasingly adopting, therefore it is essential for the automated system to be highly secure and unbreakable by any attack. For the system to be less hackable in the later years, the IT specialists are coming up with a different framework for testing security of the system, which enables the degree of vulnerability of the components or technologies that a particular smart home system pertains to.

9.4. Social Hacking

This topic is not necessarily related to smart home alone, in fact, based on the research conducted, no literature that tackles this specific issue in the context of smart homes could be found. However, I believe that this aspect is decidedly important when talking about smart homes security. It is because of human nature, as explained below, why attackers may try to use this approach in order to gain access to smart home systems. First of all, the general term will be explained and then a possible use case relevant to smart homes will be presented. Social hacking is generally termed as ‘social engineering' which means social manipulation resulting in exploitation of human characteristics as one attempts to persuade the victim to act in a manner desired by the attacker. Social engineering is currently defined as a methodology that allows an attacker to bypass technical controls by attacking the human element in an organization. There are many techniques commonly used in social engineering including but not limited to impersonation, phishing email messages, bribery, shoulder surfing, and bribery. Hackers rely on social engineering attacks to bypass technical controls by focusing on human factors. This is especially successful because social engineers often exploit the natural tendency people have in trusting others who may look credible, deferring to authority or the reluctance to social conformity (Applegate, 2009). Dumpster diving is a favorite technique of hackers and social engineers. The attacker, in this case, relies on the fact that most people do not understand the value of the information they throw away on a regular basis. Most employees would probably not think twice before throwing away a company phone directory. In the hands of a hacker though, this information could be used for foot printing, which is the art of gathering information about a predetermined target prior to the attack in order to determine the viability of such an attack (Okenyi & Owens, 2007). Information found during dumpster diving can facilitate other social engineering attacks as well. The company phone directory found above can be used to assist impersonation attacks via telephone potentially giving the attacker both target phone numbers and the names of persons to attempt to impersonate. There are many factors that contribute to the success of social engineering attacks. One of the most prominent factors is the concept of trust. People feel an inherent need to trust others, especially in a business setting. People tend to trust those they like or those they perceive as being credible. Establishing trust through likeability or credibility is one of the first things a social engineer will attempt to do, introducing themselves as someone the victim will assume is credible will maintaining an affable disposition. Another tactic that social engineers often employ is the use of authority, fear and reprisal. Attackers will often rely on a person’s tendency to be obedient to authority to gain access to critical information. Fear tactics or threats of reprisal will often also work against these types of people. These types of fear tactics are often used in phishing attacks where the subject line declares some form of security alert that the victim must respond to in order to avoid repercussions. In one of the few empirical studies conducted on the psychology behind social engineering, Michael Workman (2007) noted that people who demonstrate high levels of obedience to authority or those who trust very easily are far more susceptible to social engineering attacks. (Applegate, 2009).

Based on this knowledge, one can easily apply these aspects to the topic of smart homes in the private sector. Let us assume for instance that one smart homeowner has a valid contract for 24h /7-day troubleshooting and maintenance with a company involved in this business. Now let us imagine that an attacker identifies this relationship between the client and the company, for example just by observation, as the company employee is visiting the client for some system maintenance. In this situation, he has the possibility to call the targeted owner and pretend to be the troubleshooting company mentioned before. By using techniques described above (for instance by inducing fear, supposing that the smart home system needs to be urgently updated in order to avoid a disaster or even a hacker attack) and relying on the human factors already mentioned, he can expect to gain sensible information or even the remote login data to the automation system of the targeted house. The fact that smart home systems are getting more and more complex and so technically non-savvy persons need to rely on other specialists (Leitner & Harper, 2015), only adds to the risk caused through social engineering.

9.5. Internet of Toys and their Privacy

Web associated objects (known as the 'Web of Things') are progressively coming into our homes, with articles, for example, watches, ice chests, toothbrushes, or espresso machines, transforming our homes into Smart Houses. Among the recently associated well-known articles are additionally internet connected toys that guardians today are beginning to decide for their kids. Web associated toys can offer new, essential open doors for play, learning, wellbeing and instructive help, because of their intuitive and customized highlights. Furthermore, because these devices are likewise connected to the same network as other IoT devices, they can deliver valuable data to the automatization ecosystem of the house. However, they likewise bring up issues about security, privacy, trust and other principal privileges of youngsters. In order to assure the normal operation of these toys, similar to other IoT gadgets, they may record individual data regarding the kids' daily life and routine. In a period of worries about web wellbeing, protection and social development, it appears to be critical making a stride back, suggest conversation starters and take a gander at these associated toys, portrayed as the 'Web of Toys', from different points (Chaudron et al., 2017). In any case, as the toys used by the internet might be furnished with different sensors that can record youngsters' regular communications, they can present genuine security and protection dangers to kids. In reality, in the ongoing years, a few shrewd toys have been accounted for to be powerless, and some related organizations likewise have endured substantial scale information ruptures, uncovering data gathered through these toys. To supplement late endeavors in dissecting and measuring the security of brilliant toys, in this work, it was proposed, a thorough explanatory structure dependent on 17 protection touchy criteria to efficiently assess chosen protection parts of shrewd toys. Perceiving these interesting dangers to kids, governments and administrative experts in various districts are presenting particular laws/acts, e.g., the US Children's Online Privacy Protection Act (COPPA); or see likewise the EU General Data Protection Regulation (GDPR). The absence of effectively available protection strategies and intricacy of the approaches ruin guardians' capacity to comprehend the potential dangers of keen toys and friend applications for their youngsters. The office of the Privacy Commissioner of Canada (OPC) offers for instance rules on how data identified with kids can be gathered. As indicated by OPC, accumulation, use and sharing of data about youngsters under 13 years old, must be endorsed by their folks. In any case, in an ongoing report (McReynolds et al., 2017) guardians were observed to give careful consideration to security admonitions previously enabling their youngsters to play with toys with referred to issues, for example, Hello Barbie. None of the toy partner applications accomplish reasonable-consents. So, the present static examination uncovers diverse dimensions of over-benefits (i.e., more consents pronounced in the Manifest than the application required or utilized). For instance, Smart Toy Monkey and CogniToys Dino pronounce just a single unused authorization, however, Zenbo has 12 unused consents. Among the announced and utilized consents, there are various occurrences where the requests for authorizations are redundant for the toys' proposed working. For instance, Sphero BB-8 requires access to the surmised area; Zenbo asks for

62 consents to permit dealing with clients' records on the gadget. Static examination likewise demonstrates that some toys may perform undesirable/suspicious exercises secretly. There were however few issues in the security practices of these keen toys, particularly with respect to Personal Identifiable Information (PII) accumulation, outsider information sharing, web following, and information stockpiling location. The investigation expanded the approach by statically breaking down the toys' buddy applications to decide over-benefits, delicate PII gathering, and suspicious practices. It was found that all the buddy applications are over-advantaged and gather pointless individual data. These findings show by this, potential suspicious exercises of the friend applications, for example, manhandling the communication administration (Mahmoud et al., 2018).

9.6. Conclusion & Outlook

A key feature of the emerging smart home is the integration of heterogeneous technologies, including multiple standards, protocols, and platforms. However, the integration may introduce critical security vulnerabilities, due to the customizations, unsatisfied assumptions and incompatibilities of the technologies. Hence, it is necessary to address the security problems in smart home systems from an integration perspective, as a complement to existing studies that focus on the analysis of individual system components or technologies (Mahadewa, 2018). Likewise, one cannot omit the fact that the competition between vendors and multiple incompatible standards leads to difficulties in achieving security and a higher level of privacy. This ultimately leads to a scattered market situation (Jacobsson et al., 2016). On the other side, based on my own conducted survey (see 2.2), I was surprised to find out that the market is not really aware or concerned about these serious risks actually present in the commercial products. For instance, one company didn’t offer any further updates as soon as the system was up and running in the building, claiming that “there is not much that can get broken or can be hacked”. However, the “smart nature of these homes raises obvious security concerns and history has shown that a vulnerability in only one component may provide the means to compromise the system as a whole” (Ramljak, 2017). The question then arises: what can be done? Should we then completely avoid smart home systems because of their security flaws? Or should we simply omit these concerns at all and deploy such systems, giving that “there were no reports about serious security incidents”, as one interviewer from the survey pointed out? In my opinion, we are not allowed to give up on the smart home concept and likewise, the related issues in this chapter should not be considered as a deal breaker, but rather as a call to raise awareness and to implement well known and documented strategies which will minimize the security flaws presented in the chapter above. In correspondence to my intent, (Lee et al., 2014) summarizes various ways that can mitigate security concern from the technical perspective: • User Authentication: Many gadgets with Internet availability, requiring programming refreshes, security patches, and information trades will be conveyed in keen homes. All these procedures should be performed by approved clients just: without solid client validation, a shrewd home won't be sheltered from aggressors. • Device Authentication: A savvy home system must be shielded from forgone nodes' attack. Gadget verification will give the capacity to recognize genuine gadgets from unapproved gadgets in the automated home system. • Network Monitoring: Since the DoS attack can focus on the system layer conventions running on an automated home system, it is central to have an intrusion identification framework and checking device to distinguish arrange interruptions and report traffic inconsistencies. • Secure Key Management: Since few of the sensor gadgets are sent with pre-introduced system keys, it is required to have a safe key-administration plan to shield the smart home from aggressors that traded off gadgets inside the system. • Physical Protection:

Electronic gadgets are regularly left unattended, getting to be powerless against altering assaults. In this manner, physical insurance is one of the critical prerequisites for smart homes. Alter safe gadgets or hostile to figure out plans would be arrangements against altering assaults. Additionally, to this listing, based on my findings I would like to extend it with one more subpoint: • Retrospect updates: By maintaining an up-to-date system, newly discovered backdoors or system flaws can be eliminated. On the other side, from a social perspective, present and feature smart home users need to be more informed and trained to be able to manage and collaborate in a correct manner with such smart agents. As mentioned in the sections above, this is crucial because humans by themselves can represent a weak link in the process of maintaining the system at a secure state. These are not necessarily new or innovative ideas, but rather concepts well known from other application fields, that can be successfully implemented in the topic addressed in this work.

10. SUMMARY AND OUTLOOK Initially smart home systems were perceived as luxurious acquisitions for domestic buildings. Given the big investments involved, this led to the result that the penetration of the market by smart home systems remained low for decades. But as smart home technologies advance, they get more affordable, which in turn leads to a lesser concern regarding its price but to a higher emphasis on the usability. During the initial research conducted for this thesis, it seemed that several studies recognized different inhibitions that may have led to an unexpected low rate of smart home implementations worldwide. These results were also supported by the findings I made throughout the projects I was involved with in the last years. Based on this knowledge, I have chosen to focus in this thesis on six main aspects of smart home technologies, in order to analyze strengths, challenges and shortcomings regarding their usability. In the first part of the thesis, two chapters presented the state of the art and the most common technologies and architectures of smart homes. The following three chapters discuss the first three non-technical aspects from a social, user and environment centered perspective. The latter three chapters address three technical subjects known to be of significant influence to the usability of smart home systems, namely, interoperability, open sourcing and security. From a non-technical point of view, smart homes are technologies domesticated in order to blend in our social life, aimed to make human life more efficient and meaningful. The term ‘blend’ used in this context suggests some important aspects. First, technologies have to synchronize with daily life, while avoiding distraction or disruption from daily activities. On the contrary, their aim is to become agents who support humans along the different phases of life. Further, technologies should support social interaction between individuals, and so help groups and families in reaching different goals. For this reasoning, firstly, the impact of smart homes on human life and their interaction with computers as well as with other humans were treated. Secondly, in order to focus on special human needs, it is important to define which social groups smart homes aim to target. Lastly, the challenges were discussed, that arise through deployment of smart home technologies, more precisely, they were analyzed from the perspective of social disruption. Findings show that there is potential in improving this aspect, to achieve a better acceptance among home owners. A further aspect that influences the usability, is the financial side that smart homes are inferencing. These can be either short-term or long-term costs. In conclusion, the findings show that regarding short term costs smart homes are available for low as well as for high budgets, the main difference being not the functionality, but the after sale supports, user friendliness and the predefined and pre-implemented smartness. The long-term costs were divided into three categories: energy, maintenance and switching costs. Based on some simple calculations and statistics, it was shown that consumption costs are not the main issue in energy saving. Thus, researchers should rather focus on energy management (HEMS) solutions, as there is a higher potential for energy saving in that area. Regarding maintenance costs, research results show that there is a lack of focused study and discussion on this subject. However, from a general perspective, expensive systems tend to offer better maintenance support along with higher costs for such services. Low cost systems on the other side score with support through online platforms, thus targeting technical enthusiasts. Smart homes are also the newest frontier for green living. On this basis, the consequent section discussed about the presence or lack of approaches that should help humans to positively impact the environment by promoting eco friendliness. It was shown that, human behavior must be adapted to benefit from this new technology as it is not enough to have systems which inform the consumer about his/her eco- expensive habits. Despite realizing the potential benefits of smart home technologies, not all technologically equipped households are green smart homes. Regarding technical aspects one crucial aspect which impacts the usability is the ability of smart home technologies to interact with other systems on a M2M level. Interoperability will enable collaboration of applications and offer end users greater flexibility in choosing the desired services. There are many ways to achieve this aspect, but it is hard to convince the market to go in only one direction. Consequently, solutions were presented to prove that they can overcome this issue. Nevertheless, these approaches are just at a proof of concept level and the market must catch up with these solutions and ideas. Based on my best knowledge, I conclude that the most promising approach is to move away from platform-dependent 65 interoperability implementations, to a more general framework, for instance, the IP-based platform. This will offer the ability to be easily extended in the future without being forced to adapt, change or purchase new hardware, as it is the case with platform specific gateways. A further technical aspect discussed in this thesis, is the availability of open sourced approaches regarding smart homes. The findings show that there are a few working examples out there. But beyond the promising concept of open source, the well-known deployed solutions are closed source technologies which are using (at least partially) proprietary approaches that cannot be adapted easily to the customer’s needs. Therefore, users must stick to predefined sets of customizations the vendor is offering out of the box. The biggest drawback of open source solutions is however that in most cases they can only be set up and customized by technical skilled persons. This is because of the nature of such systems, as they do not operate in a plug-and-play fashion. Further, in the conducted research, only one project was found to be offering not only software but also hardware which is open sourced. The other systems can be more likely seen as tool-sets, libraries, or frameworks which give the end user a basis designed to help him create his own customized home automation ecosystem. Finally, security in smart home systems can be perceived as a shell that covers all aspects of such technologies. This aspect tends to be neglected in different solutions, but as domestic technologies aim to blend in our daily life improving and securing it, if they are not protected and secured by themselves, they will rather become danger and harm factors, instead of fulfilling their intended purpose. Also, the competition between vendors and multiple incompatible standards leads to difficulties in achieving security and a higher level of privacy. Further, the market is not really concerned about these serious risks present in the commercial products, as concluded from conducted interviews. There was also a lack of retrospect updates identified. Thus, as soon as new backdoors and flaws are discovered, systems remain exposed to these weaknesses. This is especially critical when radio frequencies that can be externally accessed are involved. Consequently, awareness should be increased to implement well known and documented strategies which will minimize the security flaws. Such approaches can already be addressed, without the need to reinvent the wheel, as they are already present and successfully used in other disciplines. Summarizing all these aspects, further conclusions along with topics for potential future analysis and study were presented: - It seems that there is little interest regarding the long-term operation, maintenance and the lifecycle of smart homes. Therefore, a focused research on this topic would be appropriate. - Throughout the present work, the subject of frequencies, including approvals and licenses, was not addressed in particular. In a time of globalization and standardization, this aspect deserves a closer examination, as different countries around the globe are ruled by different regulatory mechanism and policies. - As one looks closer to the subjects regarding social and environmental impact, two principles that may seem contradictory can be identified. One principle suggests that behavior should not be influenced by technology, hence it should not allow social disruptiveness. The other suggests that technologies should promote different behavior changes, with the aim to lower the carbon footprint. Consequently, it would be interesting to further analyze these aspects in order to understand and find solutions which would incorporate both principles in a harmonized way. - Regarding usability, the matter of user interfaces can pe elaborated in particular, because it represents the bridge between humans and technology. The study can focus on finding original motifs that, for instance, lead to the situation of users being overwhelmed with the operation of this technology. The improvement of the user interface may also have a more efficient impact in the user’s daily life to assist and help him in changing behaviors that are known for causing harm to the environment. Even if initially manufacturers, associations and electrical installers predicted that, in the shortest time, classical electrical installation will be almost completely discontinued in favor of intelligent automation systems, the present reality proved the contrary, confirming the skepticism of different researchers as that of Leitner & Harper: “The ﬁrst time I observed the industry and media proclaiming a golden age of smartness, I was skeptical that these things could work out in such a simple way, and I think I was right. Although much research has been done in that area, there is still a long way to go.” (Leitner & Harper, 2015)

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STATISTICS ON PUBLICATIONS AND GENERAL INTERESTS

A.1. Number - Scientific Publications from 2007 to 2018 by Web of Science Topic “smart home”

Fig. 24: Number of Scientific Publications in the last 12 years on topic “smart home” (Generated on webofknowledge.com on 2019-02-25)1

Topic “IoT”

Fig. 25: Number of scientific publications in the last 12 years on topic “IoT” (Generated on webofknowledge.com on 2019-02-25)

1 Resource is dynamic and cannot be retrieved online at a later point. 77

Topic “IoT” AND “smart home”

Fig. 26: Number of scientific publications in the last 12 years2 on topic “IoT” AND “Smart Home” (Generated on webofknowledge.com on 2019-02-25)

Title “IoT” OR “smart home”

Fig. 27: Number of scientific publications in the last 12 years with title “IoT” OR “Smart Home” (Generated on webofknowledge.com on 2019-02-25)

2 No such data available between 2007 and 2010 78

A.2. General Interests Based on Trends of Search Engine Google Trends Comparison of terms ‘Smart Home’ & ‘IoT’ between 2007 and 2018

Fig. 28: Comparison of search trends for 'smart home' & 'IoT'3 (Data source: Google Trends (https://www.google.com/trends) GENERATED ON: 2019-02-25)

3 100% represents the highest occurrence in the data. The exact number of searches could not be retrieved 79

Comparison of countries for term ‘Smart Home’ between 2007 and 2018

Fig. 29: Searched term ‘smart home’ compared between regions worldwide (Data source: google trends (https://www.google.com/trends) Generated on: 2019-02-25)

Comparison of Countries for Term ‘IoT’ between 2007 and 2018

Fig. 30: Searched term ‘IoT’ compared between regions worldwide (Data source: google trends (https://www.google.com/trends) Generated on: 2019-02-25)

OWN CONDUCTED SURVEY

B.1. Defining Questions

Following list enumerates the questions chosen for the interview: 1. Which Technology do you work with; Central/Decentral, Bus/Network? 2. What security solution your technology implements? Did you hear about any security breaches? 3. Do the technologies you offer and/or produce offer interoperability with other systems (natively)? 4. Do you offer Open Source solutions? 5. Do you offer Troubleshooting Service contracts (7days/24h)? 6. Other thoughts about smart homes? (notes taken while free discussion) In the interview artifacts, the number to the answer represents the question asked

B.2. Interviewed Companies

Company Type

1 Abb AG Production & Sales 2 ABUS Austria GmbH Production & Sales 3 Albrecht Jung GmbH & Co KG Production 4 ATsmarthome360 GmbH Sales 5 Busch-Jaeger Elektro GmbH Production 6 Capro GmbH Sales 7 EURO UNITECH Elektrotechnik GmbH Sales 8 evon GmbH Production & Sales 9 Gira Giersiepen GmbH & Co KG Production & Sales 10 S. Siedle & Söhne, Telefon u. Telegrafenwerke OHG Production & Sales 11 smart:ex Haustechnik & Elektrotechnik / Siblik Smarthome Sales 12 SpeedTech Save & Cool GmbH Sales 13 VELUX Österreich GmbH Production

B.3. Interview artifacts4

4 The interview artifacts were randomly inserted, without representing a specific order. Further, the company names were intentionally hidden (see section 2.2) 82