Iot): Survey of Opportunities and Barriers for Iot Implementation in Portugal’S Agro-Industry

applied sciences

Article Development of Technological Capabilities through the Internet of Things (IoT): Survey of Opportunities and Barriers for IoT Implementation in Portugal’s Agro-Industry

Pedro D. Gaspar 1,2 , Carlos M. Fernandez 1, Vasco N. G. J. Soares 3,4,5,* , João M. L. P. Caldeira 3,4,5 and Hélio Silva 6

1 Deparment of Electromechanical Engineering, University of Beira Interior, Rua Marquês d’Ávila e Bolama, 6201-001 Covilhã, Portugal; [email protected] (P.D.G.); [email protected] (C.M.F.) 2 Centre for Mechanical and Aerospace Science and Technologies (C-MAST), Rua Marquês d’Ávila e Bolama, 6201-001 Covilhã, Portugal 3 Polytechnic Institute of Castelo Branco, 6000-084 Castelo Branco, Portugal; [email protected] 4 Instituto de Telecomunicações, 6201-001 Covilhã, Portugal 5 InspiringSci, 6000-767 Castelo Branco, Portugal 6 Evox, 6000-767 Castelo Branco, Portugal; [email protected] * Correspondence: [email protected]

Abstract: The agro-industrial sector consumes a significant amount of natural resources for farming and meat production. By 2050, population growth is expected, generating more demand and, consequently, more consumption of scarce resources. This challenging scenario is a concern of the European Commission, revealed in the Green Deal commitment and by the United Nations’ 12th Citation: Gaspar, P.D.; Fernandez, goal of sustainable development. Thus, organizations must increase productivity and be more C.M.; Soares, V.N.G.J.; Caldeira, sustainable as soon as possible. Internet of Things (IoT) is introduced as a solution to facilitate J.M.L.P.; Silva, H. Development of agro-food companies to be more eco-efficient, mainly facing difficulties on farms, such as food Technological Capabilities through loss and waste, best efficiency in management of resources, and production. The deployment of the Internet of Things (IoT): Survey of Opportunities and Barriers for IoT this technology depends on the stage of maturity and potential of implementation. To assess and Implementation in Portugal’s characterize companies, with respect of IoT implementation, a survey was applied in 21 micro, small Agro-Industry. Appl. Sci. 2021, 11, and medium agro-food companies, belonging to milk, honey, olive oil, jams, fruticulture, bakery 3454. https://doi.org/10.3390/ and pastry, meat, coffee, and wine sectors, in the central region of Portugal. As results, this paper app11083454 reveals the stage of maturity, level of sophistication, potential, opportunities, solutions, and barriers for implementation of IoT. Additionally, suggestions and recommendations to improve practices Academic Editor: Luca Mazzoni are discussed.

Received: 16 March 2021 Keywords: agro-food industry; IoT implementation; sustainable agriculture; smart farming; chal- Accepted: 9 April 2021 lenges and solutions; potential and barriers Published: 12 April 2021

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in 1. Introduction published maps and institutional afﬁl- iations. The agro-industrial sector uses about 20% of global land, 70% percent of water, and 32% of total energy produced [1]. Population growth is creating more demand and putting pressure on this sector. The number of global inhabitants is estimated to reach nine billion people by 2050, which means 30% more people than at present and an increase of 60% in food demand [2–4]. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This scenario is even more challenging when considering the United Nations’ (UN) This article is an open access article report on sustainable development goals. This study reveals the importance of production distributed under the terms and and consumption for humanity. However, this draws attention to the unsustainable use conditions of the Creative Commons of natural resources, with alarming numbers of material footprint growths at rates of Attribution (CC BY) license (https:// about 17% between 2010 and 2017. Another concern is electric and electronic waste, which creativecommons.org/licenses/by/ has been increasing faster than recycling can process. Another aspect is the signiﬁcant 4.0/). proportion of food that is lost along the supply chain before it reaches the consumer, which

Appl. Sci. 2021, 11, 3454. https://doi.org/10.3390/app11083454 https://www.mdpi.com/journal/applsci Appl. Sci. 2021, 11, 3454 2 of 18

can be 13.8% on average, considering after harvesting and during transport, storage and processing stands [5]. However, if loss and waste through the entire food supply chain (FSC), farming (production), postharvest, processing, distribution and consumption is considered, this number could be up one third of all food produced. It is important to highlight that food loss and waste contributes to problems with food security and natural resource management [1]. Sustainability is a broad concept that addresses most aspects of human life, playing an important role in social, environmental and economic aspects. The European Green Deal provides an action plan to reduce greenhouse gas emissions by 40%, at least, when compared to 1990, increase the share of renewable energy by 32%, and improve energy efficiency by 32.5% by increasing the efficient use of resources by changing to a clean, circu- lar economy, restoring biodiversity, and cutting pollution [6]. The EU aims to be climate neutral by 2050, and, in the next few years, this political commitment will become laws and thus a legal obligation. As such, these changes have to be considered by companies, especially micro, small, and medium enterprises (MSMEs) of the agro-industrial sector, transforming their processes to be more eco-efficient [7]. This picture leads to some questions: (1) How to improve efficiency using the Internet of Things (IoT)? (2) Are MSMEs prepared to use this technology? (3) Which are the opportunities and barriers for IoT implementation? A mixed method approach was chosen to address these questions, consisting in a combination of literature review, general interviews, and expert site visits, as well as a detailed interview, in order to carry out this research. In combination with the literature review, a survey was carried out, in two phases, to assess Portugal’s profile with respect to IoT implementation. Phase 1 was a survey devoted to assess the potential and maturity of IoT solution implementation, with twenty-one companies. In Phase 2, five companies were chosen based on the answers provided in Phase 1 to perform a detailed survey, considering a realistic project, budget, and customer expecta- tions to assess IoT implementation. This approach aims to assess, in real case scenarios, IoT opportunities and solution implementations, and to overcome the lack of information in the literature. Additionally, this sample provides an overview of the IoT status in Por- tuguese agro-industry companies, which are composed mainly of MSMEs. The results of the literature research and surveys are shown and discussed in the following sections.

2. Background The background of Portugal’s agro-industry context is provided in this section. Addi- tionally, the main results of the literature review related to IoT, applied in the agro-industry, are discussed.

2.1. Portugal’s Agro-Industry Context Portugal has about 10 million inhabitants, of which 30.1% live in predominantly rural regions, and the country had a nominal GDP of 212 billion Euros in 2019. In percentage terms, compared to the European Union with its 27 member states, the total population corresponds to 2.3%, the rural population corresponds to 3.5%, and the total GDP is 1.5%, as shown in Table1[8].

Table 1. Portugal and EU: comparative GDP, population and rural population, in 2019 [7].

Nominal GDP Region Total Population Rural Population (Million EUR) Portugal 212,303 (1.5%) 10,276,617 (2.3%) 3,176,328 (3.5%) EU 27 (100%) 13,923,343 446,824,564 90,980,718

In agribusiness, the total production value was 6.796 million Euros, with participation of crops being 61.2% and the production of animals and their derivatives being 38.8%, in 2019. In percentage terms, compared to the European Union with its 27 member states, Appl. Sci. 2021, 11, 3454 3 of 18

total production outputs corresponds to 2.0%, crops corresponds to 2.1% and total animals is 1.8%, as shown in Table2[8].

Table 2. Portugal and EU: comparative total agro-industry output, crop output and animal output, in 2019 [7].

Total Output Crop Output Animal Output Region (Million EUR) (Million EUR) (Million EUR) Portugal 6796 (2.0%) 4157 (2.1%) 2639 (1.8%) EU 27 (100%) 341,098 196,082 145,015

New technologies can be applied in the agro-food sector to provide sustainability, competitiveness and increase efficiency in different operations along all FSCs. Several studies point to the Internet of Things (IoT) as a key solution to improve an organization’s performance, unlocking the potential they already have; however, in many cases, these are hidden, not measured, not processed or even just ignored [9]. Considering the questions that this framework aims to answer, the literature review design started by the definition of keywords and the selection of scientific databases. The chosen keywords were: IoT OR “internet of things” AND review AND Agro-industry OR “smart farming” OR “precision agriculture”. The selected scientific databases were Science Direct and MDPI. Papers selection was based on the most recent five years, title analysis and content, resulting in 33 relevant publications. Additionally, some exploratory research was conducted to reinforce this research. The main results of IoT application in agro-industry are grouped by subject and summarized in Table3.

Table 3. Main results of IoT applied in agro-industry.

Main Subject of Papers Identiﬁed Papers Application of IoT in agro-industry 33 Smart farming, intelligent farming or precision agriculture 14 Monitoring, measuring, controlling and tracking 6 Artiﬁcial Intelligence, data driven decisions 5 Block chain 2 (Cyber)security 2 Big data 5 Robotics 2 Unmanned aerial vehicles (UAV) 2 Opportunities and barriers for IoT 5 Others 3 Note: The papers described above can be related to one or more categories.

The next sections highlights the main concepts related to the current study.

2.2. Internet of Things (IoT) The Internet of Things, or IoT, allows physical objects to be identified and tracked through the collection of relevant data, which will be transformed into useful information and transmitted over a network, enabling the creation of alerts for situations that may require some type of correction. This concept provides agility and visibility in tracking and sharing information, facilitating the planning and in the control of processes. Thus, an object capable of establishing connection through the Internet and that communicates with other objects in a network is considered a “thing”. Its application can improve efficiency in several fields, such as, households appliances, electronics, furniture, agriculture, industrial machinery [10,11]. In general, IoT architecture is composed of four layers, considering the main components of IoT solutions: perception, transport, processing and applications. • Perception/smart device: this layer enables to connect physical devices in a digital network, allowing real-time information to be collected and processed. Sensors can Appl. Sci. 2021, 11, 3454 4 of 18

perform measurements of temperature, air quality, speed, humidity, pressure, flow, movement, electricity, etc. • Transport: after measurements are done, the results must be transmitted. This layer enables Internet connection through networks and protocols, such as WiFi, global system for mobile communications (GSM), Bluetooth, etc. • Processing: the collected and transmitted information becomes data and needs to be stored, filtered, processed, and analyzed. • Application: this is the interface layer, allowing monitoring, decision-making, controlling, regulating, command, etc. Concepts are changed when, for example, they are applied to agriculture, turning a simple a farm into a smart farm. Some other authors refer to IoT with three layers [12] and others with five layers [13].

2.3. Smart Farming and Precision Agriculture Smart farming can be understood as the application of supplementary technologies to agricultural production techniques to help minimize waste and increase productivity. The application of IoT in farming allows to boost the production process through plantation monitoring, soil and water management, irrigation scheduling, pest control, delivery tracking; using data from temperature, luminosity, humidity, pressure, ground chemical concentration, and images, which are collected by sensors and cameras, using unmanned ﬂying equipment (UAV), agricultural information management systems, global positioning systems (GPS) and communication networks. This integration results in the optimization of scarce resources. Precision agriculture has its concept linked direct to precision, which means, to manage precisely resources, such as energy, soil, water, fertilizers, herbicides and pesticides, among others, using different methods and techniques [14]. To achieve the best management, the most correct information is fundamental. Thus, IoT is noted as a solution to optimize agriculture and for precision agriculture.

2.4. Unmanned Aerial Equipment (UAV) or Drones One of the most versatile IoT devices are the Unmanned Aerial Equipment (UAV). This unmanned vehicle is usually composed of a ground controller and a communication system. Usually, its function in agriculture is related to aerial surveillance in precision agriculture for monitoring weeds, vegetation growth, irrigation, crops, etc. [15]. To enhance system efficiency, other technologies can be aggregated, such as artificial intelligence (machine learning or deep learning), mobile edge computing, and software-defined networks [16]. Associated with specialized sensors, UAVs are becoming powerful sensing systems that complement IoT-based techniques [15].

2.5. Artificial Intelligence/Data Driven Decisions The use of IoT brings a huge amount of information and variables. This information must be treated, otherwise it is useless. The process for optimization includes system modeling, which sometimes is difficult due to the number of variables. There are algorithms that are specialized to overcome these difficulties. In the agro-industry, the most common are deep learning and machine learning, based on big data. An example is the greenhouse microclimate, which is complex, multiparametric, non-linear and depends on a set of external and internal factors. Artificial neural networks have been used to reduce energy consumption [17]. Other artificial intelligence (AI) applications are related, for example, to the detection of diseases in crops, to distinguish plant or flower types [18], optimization for UAVs [16], and the detection of insects [19].

2.6. Big Data As result of collecting data from different sources, a huge set of data is generated and is combined as big data [9,20]. From the farmer’s perspective, big data can add value to decision making. Data processing and analytics involve the transformation of farm decision Appl. Sci. 2021, 11, 3454 5 of 18

making, from a traditional decision to a precise data-driven decision [21]. However, the data have some challenges, related to their transmission, storage and processing security. Block chain is noted as a technology that can improve security. Despite large opportunities due to digitalization and digital tools to boost productivity and environmental improvement, they are limited by some issues, including data governance, a lack of skill in how to handle and interpret data, and unclear return on investments in new technologies, from farmer’s point of view [9].

2.7. Block Chain The block chain concept is based on a decentralized, distributed ledger for storing time-stamped transactions between many computers in a peer-to-peer network. Thus, any involved record cannot be tampered with retroactively. This concept allows block chain users to audit and verify transactions, independently and transparently. Nowadays, this technology is applied in cryptocurrencies, processing records called “blocks”, which are connected using cryptographic techniques. Each block must have a hash code of the previous block, a timestamp, and a set of conﬁrmed transactions [22,23]. This technology has many applications in precision agriculture and/or smart agriculture. The adoption of IoT brought a need to develop smart peer-to-peer systems capable of verifying, securing, monitoring, and analyzing agricultural data. These data must be secure and reliable. Block chain is changing the classical methods of storing, sorting and sharing agricultural data into a more reliable, immutable, transparent and decentralized manner. However, the adoption of blockchain in smart farming or precision agriculture still needs to mature to become a reality. Currently, there are several projects using this technology. A total of 40% are in the concept phase, 53% are in the pilot phase, and 7% do not have available information [22,23].

2.8. Robotics Agricultural activities involving robotics exhibit a high degree of technology and autonomy to perform tasks. This degree of autonomy between a simple IoT device and a robot differs. Currently, most common applications in agriculture are linked to harvesting and weeding, followed by diseases detection and seeding [14]. Technological advances in machine vision, GPS, laser technologies, actuators, and mechatronics have allowed the implementation of robotic systems in agro-industry [24]. Several robotic harvesting systems have been developed for cucumber, strawberry, tomato, asparagus, grain, lettuce, mushroom, and orange crops, among others. Additionally, the integration of IoT, cloud computing and robotics is developing rapidly. Several sensors are applied in robotics, machine vision being one of the most important. Unfortunately, the number of applications completely developed which are used in real scenarios is still limited [12].

2.9. IoT in Agriculture IoT applied in agriculture can reshape all concepts, transforming traditional farming into smart farming (or Agriculture 4.0). It uses different types of sensors to collect data (e.g., temperature, humidity, light, pressure, presence, etc.), and enables precision agriculture. Precision agriculture uses data-driven decisions with a base of information technology to ensure that crops and soil receive exactly what is necessary for optimum heathy and productivity [10,25–31]. Figure1 summarizes most of the challenges in farming and livestock production, subdivided into monitoring, measuring, tracking, and controlling. The most important and common variables for production are connected to each of these sections. On the right side, different approaches based on IoT solutions through digitalization of a “thing” [32] are shown. Each of these solutions can generate a huge amount of data, called big data [33,34], which is collected in real-time and processed by optimization AI-based algorithms for data driven decisions and other technologies [16,17], aiming at monitoring, measuring, tracking or controlling, allowing to improve production results [10,11,13,15,18,19,24,25,35–44]. Block chain is an emerging technology and is con- Appl. Sci. 2021, 11, 3454 6 of 18

sidered a solution for the cybersecurity of IoT devices [22]. Several approaches like robotics are considered as solutions as well [12,14].

Figure 1. Main challenges and IoT solutions.

In the rest of the FSC, IoT can signiﬁcantly reduce constraints, loss and waste during postharvest, processing, distribution, and consumption. While in postharvest, processing and in distribution, improvement is mostly linked to logistics; in the consumption level, it could change a consumer’s perception or behavior, using intelligent packaging. In all FSCs food loss and waste can be reduced with the implement of IoT [45]. Despite of all beneﬁts that IoT technology can bring to organizations, as previously noted, the main barriers for its implementation from a MSME farmer’s perspective are infrastructure, knowledge, costs, risks, and cybersecurity. Most papers point to IoT as a solution and discuss technical issues and applications related to it. Just a few papers consider a farmers’ reality in a generic approach. This research is summarized in Table4[4,11,46]. Thus, the best results and success depend, not only on the application of IoT, but also on the approach, choosing the right solution according to an organization needs. Thus, it is very important to discover an actual framework for MSME farming organizations in the central region of Portugal, and answers research questions 2 and 3. To assess the sophistication and the potential for IoT transferability for companies, a survey was carried with 21 organizations. Additionally, 5 companies were be chosen for a more detailed survey. Thus, this study reveals the maturity stage, sophistication, potential, opportunities, solutions and barriers of IoT deployment, through a case study performed in the central region of Portugal, within the scope of the project Development of Technological Capabil- ities for the Industrial Application of the Internet of Things (IOTEC) [47]. The results of the survey and discussions will be presented in subsequent sections. Section3 includes a description of the Materials and Methods. It includes details of the two-step survey. The sample characteristics are provided, as is the structure of each questionnaire. Section4 presents the results and includes a discussion. It includes an analysis of the Phase 1 survey, devoted to assessing the potential and maturity of IoT solution implementation, as well as the Phase 2 survey to the assess a real scenario of IoT opportunities and solution implementation. Section5 provides some suggestions and recommendations for the digitalization Appl. Sci. 2021, 11, 3454 7 of 18

of the agro-food companies, based on an analysis of the results of the surveys. Section6 describes the main conclusions of the study.

Table 4. Brief description of main IoT challenges (adapted from [4,11,46]).

Barriers Brief Description Operational risks are related to natural causes, such as animal attacks, rain, lightning, or even regular maintenance, could cause stoppage at a farm. (Cyber)security Additionally, hacker attacks are linked to accessing sensitive information, hijacking cloud information or databases, or even blocking wireless signals. Implementation and operation are the main costs for IoT in agriculture. The implementation costs consist of hardware costs, such as IoT devices/sensors, base station infrastructure, and gateways. Furthermore, Cost running costs include an uninterrupted subscription for the management of IoT devices, the exchange of information among other services, and centralized services that provide information/data collection. Most farmers are uneducated in IoT, which creates a great barrier to understanding how technology could contribute to improve production. Lack of knowledge Furthermore, it increases the costs of training to qualify people to use IoT on their farms. Several IoT devices, standards and protocols are necessary to enable Interoperability communication between devices from different manufacturers.

3. Materials and Methods To assess the current state of agro-industry with respect to IoT implementation for companies in the central region of Portugal, a survey was selected as the methodology, which was divided in two steps, each one with its own objectives and activities, as shown below: Phase 1: Assess the potential and maturity pf IoT solution implementation. • Deﬁnition of sample; • Structuring script; • Conducting interviews; Phase 2: Assess real scenario for IoT opportunities and solution implementation. • Selection of ﬁve companies for a deeper questionnaire to assesses opportunities and constraints of IoT implementation.

3.1. Phase 1: Assess the Potential and Maturity of IoT Solution Implementation An inquiry with several questions was made to assess the potential and maturity of IoT solution implementation. Additionally, the survey reveals the sophistication of interviewed companies. Detailed information about each step is shown in subsequent sections.

3.1.1. Definition of the Stratified Sample of Agro-Food Companies The initial stage included the following methodological tasks: • Limit of the sample of agro-food companies for questioning; • Creation of an “Alternative Business Exchange”, in order to ensure, in due time, eventual failures/possibility of refusing to answer and/or last-minute impossibili- ties/imponderables of the pre-selected sample, even after due diligence of (re)confirmation; • Survey and validation of e-mail contacts from the group of companies in the agro- food sector, in order to guarantee a sample with validated responses from at least 21 companies in the central region of Portugal. As the cluster of agro-industrial organizations of the central region in Portugal, Inov- Cluster’s associates were potential companies for this part of the study [48], which was also in line with IOTEC project objectives. The contact list was analyzed, and after starting Appl. Sci. 2021, 11, 3454 8 of 18

the survey it was veriﬁed that some contacts no longer corresponded to the initial phone numbers and some of the initially contacted companies were closed. Notwithstanding these constraints, the information provided, associated with the adopted survey method, enabled an important methodological advance, namely allowing the survey to be directed to all companies that fell into the desired category and whose headquarters were located in the central region of Portugal. These options increased the likelihood of obtaining more favorable response rates and guaranteed representativeness in the sampling process. Figure2 shows the percentage of small businesses in the subsector of the agro-food segment surveyed in the central region of Portugal.

Figure 2. Distribution of surveyed companies by sector of activity.

It was veriﬁed that most of the companies that were made available to collaborate in the characterization study belonged to the dairy sector, followed by the olive oil and honey sectors. Additionally, information about company sizes is shown in Figure3. Half of the companies surveyed were micro-enterprises with fewer than ﬁve employees, with 40% of the companies being from the small business category. Only 10% of companies surveyed already had a size, considering the number of workers, which corresponded to a medium- sized company. This result highlights the reality of the agro-food industry, not only in the central region, but also in the whole country, which is composed mainly of micro and small enterprises, many of them being family businesses.

Figure 3. Distribution of surveyed companies by workers.

The main constraints found in the course of the study were: • Different segments, processes and work shifts cause difﬁculties in making contact. As example, the productive section of bakery and pastry companies work during night Appl. Sci. 2021, 11, 3454 9 of 18

limiting the contact possibilities. Additionally, in agricultural activities, the work shift is during the day, without interruptions. In both cases, there are difﬁculties in contacting via telephone as well as with scheduling; • Reduced sensitivity to the issues raised, as the business fabric in these sectors, with numerous family holdings, shows a strong dismay or perception of the issues at stake (low qualiﬁcations and advanced age of those/workers, learning from work itself). After overcoming these constraints and validating the contacts, the survey was conducted in person or by telephone.

3.1.2. Structuring the Script and Building the Questionnaire This stage comprised the deﬁnition of the script for face-to-face/telephone interviews, supported by a multitude of issues directly related to the sophistication of companies in the agro-food sector and their appetite for the use of multimedia tools. The survey consisted of 31 questions that aimed to enable the characterization of the sophistication of agro-food companies and their production process. The interviews were held throughout 2018. This stage focused on the face-to-face and telephone interview process. We tried to establish a procedure for the collection of information via telephone, and face-to-face interviews were used when phone contact was impossible or interviewees were unavailable. After compiling the 21 carried out face-to-face/telephone surveys, the data were collected with an online application in a comma-separated values (CSV) format, compatible with spreadsheet software, and were exported.

3.2. Phase 2: Assess Real Scenario for IoT Opportunities and Solution Implementation The main objectives of this topic were to identify, by sector of activity, which parts of companies received more investment, potential for implementation of IoT, identiﬁcation of opportunities, budget, return of investment, and expected results in order to assess if the project was realistic within a company’s budget and calendars. In addition, to identify the main implementation restrictions. Selection of 5 Companies to Deeper Questionnaire Assessing Opportunities and Constrains of IoT Implementation This selection was made based on the previous questionnaire, which showed differ- ences in company maturity. However, this criterion was not the only one considered, since even companies with a low maturity show high potential for transferability of IoT. The IoT implementation process should start gradually and incrementally over a period of time, and between 6 months and 2 years, depending on the maturity of the company, may be necessary. The main objectives of this questionnaire were to identify, by activity segment, which parts of companies receives more investment, potential for implementation of IoT, identiﬁ- cation of opportunities, budget, return of investment, and expected results, according to the state of each company. A survey of the opportunities was carried out by contacting the selected companies that, based on the questionnaire, were selected: Delta Cafés, Massimo Zanetti Beverage Iberia, Fumeiros da Guarda, Sabores da Guarda and Claro’s Beekeeping.

4. Results and Discussion 4.1. Phase 1: Assess the Potential and Maturity for IoT Solution Implementation A compilation of questionnaire answers is described in this section. Only the most relevant data are presented, analyzed, and discussed, as shown in Table5. The results are divided into topics, as is the survey. Percentage was chosen for a better understanding and comparison. Appl. Sci. 2021, 11, x FOR PEER REVIEW 10 of 18

Appl. Sci. 2021, 11, x FOR PEER REVIEW 10 of 18

Appl. Sci. 2021, 11, x FOR PEER REVIEWSelection of 5 Companies to Deeper Questionnaire Assessing Opportunities and Con-10 of 18 strains of IoT Implementation Appl. Sci. 2021, 11, x FOR PEER REVIEWSelection of 5 Companies to Deeper Questionnaire Assessing Opportunities and Con-10 of 18 strainsSelectionThis of ofselectionIoT 5 ImplementationCompanies was made to Deeper based onQuestionnaire the previous Assessing questionnaire, Opportunities which showed and Con- differ- Appl. Sci. 2021, 11, x FOR PEER REVIEW 10 of 18 encesSelectionstrainsThis in of company ofselectionIoT 5 CompaniesImplementation maturity. was made to However,Deeper based Questionnaireon this the criterion previous Assessingwas questionnaire, not the Opportunities only whichone considered, showed and Con- differ- since Appl. Sci. 2021, 11, x FOR PEER REVIEWeven companies with a low maturity show high potential for transferability of IoT.10 ofThe 18 strainsencesSelectionThis in of company ofIoTselection 5 ImplementationCompanies maturity. was made to However,Deeper based Questionnaireon this the criterion previous Assessingwas questionnaire, not the Opportunities only whichone considered, showed and Con- differ- since IoT implementation process should start gradually and incrementally over a period of Appl. Sci. 2021, 11, x FOR PEER REVIEWevenstrainsences Thiscompanies in of company selectionIoT Implementation with maturity. was a madelow However, maturity based on showthis the criterion prev highious potential was questionnaire, not forthe transferabilityonly which one considered, showed of IoT. differ-10 since ofThe 18 time,Selection and ofbetween 5 Companies 6 months to Deeperand 2 years, Questionnaire depending Assessing on the maturity Opportunities of the company, and Con- may Appl. Sci. 2021, 11, x FOR PEER REVIEWencesIoTeven implementation companiesin company with maturity. process a low However, maturityshould start thisshow criteriongrad highually potential was and not incrementally thefor onlytransferability one considered,over aof period IoT.10 since ofThe of18 beSelectionstrains necessary.This of ofselectionIoT 5 CompaniesImplementation was made to Deeper based Questionnaireon the previous Assessing questionnaire, Opportunities which showed and Con- differ- Appl. Sci. 2021, 11, x FOR PEER REVIEWeventime,IoT implementation companiesand between with 6 monthsprocess a low and maturityshould 2 years, start show depending grad highually potential on and the incrementally maturityfor transferability of the over company, aof period IoT.10 mayofThe of18 encesThe in company main objectives maturity. of this However, questionnaire this criterion were towas identify, not the by only activity one considered, segment, which since strainsSelectionIoTbetime, necessary. implementationThis and of ofIoTselectionbetween 5 ImplementationCompanies 6was monthsprocess made to Deeper and should based 2 years, Questionnaire onstart the depending grad prevuallyious Assessing onquestionnaire,and the incrementally maturity Opportunities which of the over company,showed and a period Con- differ- may of partseven ofcompanies companies with receives a low more maturity investment, show high potential potential for implementationfor transferability of IoT,of IoT. identi- The strainstime,beences necessary.ThisThe and in of company main selectionIoTbetween Implementation objectives maturity. 6was months made of this However, and based questionnaire 2 years, on this the depending criterion prev weiousre towas onquestionnaire, identify, the not maturity the by only activity which oneof the considered, segment, showedcompany, differ-which since may ficationSelectionIoT implementation of of opportunities, 5 Companies process budget,to Deeper should return Questionnaire start of gradinvestment,ually Assessing and and incrementally expected Opportunities results, over andaccording a period Con- toof encesbepartseven necessary. The ofcompaniesin companiescompany main objectives with maturity. receives a low of thisHowever,more maturity questionnaire investment, thisshow criterion high wepotentialre potential wasto identify, fornot implementationthefor byonlytransferability activity one considered, segment, of ofIoT, IoT. identi- which since The theSelectionstrainstime, stateThis and of of ofselectionIoTbetween each5 ImplementationCompanies company. 6was months made to A Deeperand basedsurvey 2 years, Questionnaireon of the thedepending prev opportunitiesious Assessing onquestionnaire, the wasmaturity Opportunities carried which of theout showedcompany, by and contacting Con- differ- may evenficationpartsIoT implementation The companiesof ofcompanies main opportunities, objectives with receives process a low ofbudget, this morematurity should questionnaire returninvestment, start show of gradinvestment, high wepotentialuallyre potential to and identify, and for incrementally implementationforexpected bytransferability activity results, over segment, of according ofaIoT, period IoT. identi-which The toof strainsencesbe necessary. in of company IoT Implementation maturity. However, this criterion was not the only one considered, since theficationtime, selectedstateThis and of of selectionbetween opportunities, eachcompanies company. 6was months that,made budget, A basedand basedsurvey 2 return years,on on ofthe the of thedepending questionnaire, investment,prev opportunitiesious onquestionnaire, andthe were wasmaturity expected selected: carried which of results, the outDelta showedcompany, by accordingCafés, contacting differ- Mas- may to IoTevenparts implementation The companiesof companies main objectives with receives process a low of this more maturityshould questionnaire investment, start show grad high wepotentialuallyre potential to and identify, for incrementally implementationfor bytransferability activity over segment, of aofIoT, period IoT. identi- which The of simoencesthebe necessary. selectedstateThis Zanettiin company ofselection eachcompanies Beverage company. maturity. was Iberia,madethat, However,A based basedFumeirossurvey on on ofthisthe the dathe questionnaire,criterion prevGuarda, opportunitiesious was Saboresquestionnaire, not were was the da selected: only carriedGuarda whichone outDelta considered,and showed by Claro’sCafés, contacting differ- sinceMas-Bee- time,IoTficationparts implementation andof ofcompanies between opportunities, 6 receives monthsprocess budget, moreand should 2 return investment,years, start ofdepending gradinvestment, potentialually on and and thefor incrementally maturity implementationexpected of results, the over company, of according aIoT, period identi- may ofto keeping.encesevensimothe selected The companiesZanettiin company main companies Beverage objectives with maturity. a Iberia, that,low of thisHowever, maturitybased Fumeiros questionnaire on thisshowthe da questionnaire,criterion Guarda, high were potential wasto Sabores identify, not were forthe da selected: bytransferabilityonly Guarda activity one Delta considered,and segment, Claro’sCafés,of IoT. which since Mas- Bee-The betime,thefication necessary. state and of of between opportunities, each company. 6 months budget, A and survey 2 return years, of ofthedepending investment, opportunities on theand maturitywas expected carried of results, the out company, by according contacting may to evenIoTkeeping.parts implementation companiesof companies with receives process a low more maturityshould investment, start show grad high potentialually potential and for incrementally implementationfor transferability over of aofIoT, period IoT. identi- The of bethesimo necessary. selectedThe Zanetti main companies Beverage objectives Iberia,that, of this based Fumeiros questionnaire on the da questionnaire, Guarda, were to Sabores identify, were da selected:by Guarda activity Delta and segment, Claro’sCafés, which Mas- Bee- 4.IoTtime,thefication Results stateimplementation and of of between andopportunities, each Discussion company. 6 monthsprocess budget, A and should survey 2 return years, start of ofthedepending gradinvestment, opportunitiesually on and theand incrementally maturitywas expected carried of results, the out over company, by according a contacting period may ofto partssimokeeping.The ofZanetti companies main Beverage objectives receives Iberia, of this more Fumeiros questionnaire investment, da Guarda, wepotentialre to Sabores identify, for implementation da by Guarda activity and segment, of Claro’s IoT, identi-which Bee- 4.1.time,be4.the Results necessary. selectedPhasestate and of1:between and Assesseachcompanies Discussion company. the6 months Potential that, A andbased surveyand 2 years, Maturityon ofthe thedepending questionnaire, foropportunities IoT Solution on the were maturitywasImplementation selected: carried of the outDelta company, by Cafés, contacting Mas-may ficationpartskeeping.simo ofZanetti ofcompanies opportunities, Beverage receives Iberia, budget, more Fumeiros returninvestment, ofda investment, Guarda, potential Sabores andfor implementationexpected da Guarda results, and of accordingClaro’s IoT, identi- Bee- to be4.the Resultsnecessary. selectedThe main and companies objectivesDiscussion that, of this based questionnaire on the questionnaire, were to identify, were byselected: activity Delta segment, Cafés, which Mas- thefication4.1. statePhaseA compilation of of 1: opportunities, eachAssess company. the of Potentialquestionnaire budget, A survey and return Maturity answersof ofthe investment, foropportunities is IoT described Solution and was inImplementationexpected this carried section. results, out Only by according contacting the most to Appl. Sci. 2021, 11, 3454 partskeeping.simoThe ofZanetti companies main Beverage objectives receives Iberia, of this more Fumeiros questionnaire investment, da Guarda, wepotentialre to Sabores identify, for implementation da by Guarda activity and segment, of Claro’s IoT, identi-which10 Bee- of 18 relevantthe4.4.1. Results selectedstatePhaseA compilation dataof 1: and eachAssesscompanies are Discussion company.presented, the of Potentialquestionnaire that, A analyzed,based survey and Maturityon answers of theand the questionnaire, discussed, foropportunities is IoT described Solution as shownwere wasinImplementation thisselected: incarried Tablesection. outDelta 5. TheOnly by Cafés, contactingresults the Mas-most are partsficationkeeping. of ofcompanies opportunities, receives budget, more returninvestment, of investment, potential andfor implementationexpected results, of according IoT, identi- to dividedsimothe4.1.relevant4. Results selectedPhase AZanetti compilation intodata 1: and Assesscompanies topics,Beverageare Discussion presented, the ofas Potential questionnaire Iberia,isthat, the analyzed,based survey.Fumeiros and Maturityon answers Percentage theand da questionnaire, discussed, Guarda,for is IoT described was Solution Sabores aschosen shownwere inImplementation da thisforselected: inGuarda aTablesection. better Delta 5.and understandingTheOnly Claro’sCafés, results the Mas-mostBee- are thefication state of of opportunities, each company. budget, A survey return of ofthe investment, opportunities and was expected carried results, out by according contacting to andkeeping.simodividedrelevant comparison. Zanetti intodata topics,Beverageare presented, as Iberia,is the analyzed, survey.Fumeiros Percentage and da discussed,Guarda, was Sabores aschosen shown da for inGuarda aTable better 5.and understandingThe Claro’s results Bee- are the4.1.4. Results selectedstatePhaseA compilation of 1: and eachAssesscompanies Discussion company. the of Potentialquestionnaire that, A based survey and Maturityon answers ofthe the questionnaire, foropportunities is IoT described Solution were wasinImplementation thisselected: carried section. outDelta Only by Cafés, contacting the Mas-most simokeeping.relevantanddivided comparison. Zanetti intodata Table Beveragetopics,are presented, 5. asSummary Iberia,is the analyzed, survey. ofFumeiros applied Percentageand survey.da discussed, Guarda, was Sabores as chosen shown da for inGuarda aTable better 5.and understandingThe Claro’s results Bee- are 4.the4.1. Results selectedPhaseA compilation 1:and AssesscompaniesTable Discussion 5.the of Summary Potential questionnaire that, based of and applied Maturityon answers the survey. questionnaire, for is IoT described Solution were inImplementation thisselected: section. Delta Only Cafés, the Mas-most and comparison. simokeeping.dividedrelevant Zanetti intodata topics,Beverageare presented, as Iberia,is the analyzed, survey.Fumeiros Percentage and da discussed,Guarda, was Sabores aschosen shown da for inGuarda aAnswersTable better 5.and understandingThe Claro’s results Bee- are 4.1.4. Results QuestionnairePhaseA compilation 1: and AssessTable Discussion the5. of Summary Potential questionnaire of and applied Maturity answers survey. for is IoT described Solution Implementationin this section. Only the most keeping.anddivided comparison. into topics, as is the survey. Percentage was chosen for aAnswers better understanding relevantQuestionnaire dataTable are presented, 5. Summary analyzed, of applied and survey. discussed, as shown in(Yes) Table 5. The results (No) are 4.1.4.and Results Phase comparison.A compilation 1: and Assess Discussion the of Potential questionnaire and Maturity answers for is IoT described Solution (Yes)inImplementation this section.Answers Only (No) the most relevantdividedQuestionnaire datainto Table topics,are presented, 5. asSummary is the analyzed, survey.of applied Percentageand survey. discussed, was as chosen shown for in aTable better 5. Theunderstanding results are (1)(1) DoesDoes the the company company havehave an an4.1.4. organized Resultsorganized PhaseA compilation 1: and information Assess information Discussion the of Potential system?questionnaire system? (Network,and (Network,Maturity answers servers, for serv- is IoT described Solution (Yes)inImplementation this section.Answers Only (No) the most and comparison. 62% 38% connectivity)? dividedQuestionnaire into topics, as is the survey. Percentage was chosen for a better understanding (1) ers,Does connectivity)? the company have an4.1.relevant organized PhaseA compilation data 1: Assess Tableinformationare presented, the5. of Summary Potential questionnaire system? analyzed, ofand applied (Network,Maturity answers and survey. discussed, for serv-is IoT described Solution as shown in(Yes)Implementation this in Tablesection.Answers 5. TheOnly (No) results the most are and comparison. 62% 38% Questionnaire (2) Does the company use planningrelevantdivided and intodata decision Table topics,are presented, 5. supportasSummary is the analyzed, tools?survey. of applied Percentage and survey. discussed, was aschosen38% shown for in aTable better 5. understandingThe results62% are (1) ers,Does connectivity)? the company have an organizedA compilation information of questionnaire system? (Network, answers serv-is described (Yes)in this section.Answers Only (No) the most 62% 38% and comparison. (3)(2)(2) Doesers,Does connectivity)? the the company company recorduse use planningrelevantdivided the Questionnairerelationship and and intodata decision decision topics,are betweenpresented, support assupport is tools?thethe analyzed, tools? survey.different Percentage and items discussed, or was aschosen38% shown for in aTable better 5. understandingThe results62% are (1) Does the company have an organizedTable information 5. Summary system? of applied (Network, survey. serv- (Yes) (No) 62% Answers 38% (2) batchesDoes the used company as raw use materials planningdividedand Questionnaire comparison.and and into us eddecision topics, items asorsupport batchesis the tools?survey. of finished Percentage was chosen69% for a better understanding31% (3) Does the company record the relationship between the different items or 38% 62% (1) ers,Does connectivity)? the company have an organizedTable information 5. Summary system? of applied (Network, survey. serv- products, through computers? 62%(Yes) Answers (No) 38% (2)(3)(3) DoesbatchesDoes the the used company company as raw userecord materials planningand thethe relationship comparison.relationshipand and us eddecision items between between supportor thebatches the different tools? different of finished items items or batches or 69% 31% Questionnaire 38% 62% (1) ers,Does connectivity)? the company have an organizedTable information 5. Summary system? of applied (Network, survey. serv- (4) Performproducts,used as efficient rawthrough materials handling computers? and usedincluding items orex batchespiration of date, ﬁnished temperatures, products, through etc.? 67%(Yes) Answers (No) 33% batches used as raw materials and used items or batches of finished 62% 38% 69% 31% (3)(2) Does the company recorduse planning the relationship and decision between support the tools? different items or 38% 62% Questionnaire (1) Doesers,computers? connectivity)? the company have an organizedTable information 5. Summary system? of applied (Network, survey. serv- (5)(4) IsPerformbatchesproducts, there anyused efficient through kind as raw ofhandling computers? control materials includingto guarantand us edexeepiration itemsthe transport, or date, batches temperatures, storage of finished and exhibition etc.? 67%(Yes) Answers (No) 33% 62%69% 38%31% (3)(2) Does the company userecord planning the relationship and decision between support the tools? different items or 52% 48% Questionnaire 38% 62% ers, connectivity)? (1)(5)(4) untilproducts,IsPerformDoes there the the any efficientsale companythrough kind of the ofhandling computers? products?havecontrol an includingto organized guarant exee informationpiration the transport, date, system? temperatures, storage (Network, and exhibition etc.? serv- 67%(Yes) Answers (No) 33% batches used as raw materials and used items or batches of finished 69% 31% 62% 38% (3) Does the company record theQuestionnaire relationship between the different items or 52% 48% (2) Does the company use planning and decision support tools? 38% 62% (6)(4) Isers, therePerform connectivity)? a need efﬁcient for handlingreal-time including data collection? expiration date, temperatures, etc.? 71% 29% (1)(4)(5) untilPerformIsproducts,Does there the the any efficientsale companythrough kind of the handlingof computers? products?havecontrol an including toorganized guarant exee informationpiration the transport, date, system? temperatures, storage (Network, and exhibition etc.? serv- 67%(Yes) (No) 33% batches used as raw materials and used items or batches of finished 62% 38% 52%69% 48%31% (3)(2) Does the company recorduse planning the relationship and decision between support the tools? different items or 38% 62% (7) Is the company connected to automated production systems? 29% 71% (6) Isuntilers, there connectivity)? the a sale need of for the real-time products? data collection? 71% 29% (1)(5)(4) IsPerformDoes there the any efficient company kind ofhandling havecontrol an includingto organized guarant exee informationpiration the transport, date, system? temperatures, storage (Network, and exhibition etc.? serv- 67% 33% products, through computers? 62%52% 38%48% batches used as raw materials and used items or batches of finished 69% 31% (8)(3)(2)(6) AreDoesIs there advanced the a companyneed control for real-timeuserecord systems planning the data relationship necessary? andcollection? decision between support the tools? different items or 43%38%71% 57%62%29% (7) Is the company connected to automated production systems? 29% 71% untilers, connectivity)?the sale of the products? (5)(4)(5) products,IsPerform Isthere there any efficient anythrough kind kind handling of computers? controlcontrol toincluding to guarantee guarant ex theeepiration the transport, transport, date, storage temperatures, storage and exhibition and exhibition etc.? until 67% 33% 52% 48% batches used as raw materials and used items or batches of finished 69% 31% (9)(3)(2)(8)(7) DoesAreIs the advanced the salecompany company of the control products? connected performuserecord systems planning theto data automated relationship necessary? andanalysis decision production during between support the the systems?production tools? different process?items or 29% 71% (6) Is there a need for real-time data collection? 71% 29% 38%43% 62%57% 81% 19% until the sale of the products? (4)(5) Performproducts,Is there any efficient through kind handlingof computers? control including to guarant exeepiration the transport, date, temperatures, storage and exhibition etc.? 67% 33% batches used as raw materials and used items or batches of finished 52% 48% (8) Are advanced control systems necessary? 69% 31% (3)(7) DoesIs the thecompany company connected record theto automated relationship production between the systems? different items or 29%43% 71%57% (9) Does the company perform data analysis during the production process? (10)(6) TheIs there company a need cross-checks for real-time the data results collection? of these analyses with the traceability 81%71% 29%19% until the sale of the products? 57% 43% (5)(4) IsPerformproducts, there any efficient through kind ofhandling computers? control including to guarant exeepiration the transport, date, temperatures, storage and exhibition etc.? 67% 33% (8)(9) ofbatchesAreDoes production advanced the used company as information?control raw perform materials systems data andnecessary? analysis used items during or batchesthe production of finished process? 69% 31% 52% 48% (6) Is there a need for real-time data collection? 43% 57% 81% 19% (10)(7) TheIs the company company cross-checks connected tothe automated results of productionthese analyses systems? with the traceability 29% 71% (6) Is there a need for real-time data collection? 71% 29% until the sale of the products? 57% 43% (4)(5) PerformIsproducts, there any efficient through kind handlingof computers? control including to guarant exeepiration the transport, date, temperatures, storage and exhibition etc.? 67% 33% (9)(10)(8) ofDoesTheAre production advancedcompany the company information?cross-checkscontrol perform systems thedata necessary?results analysis of these during analyses the production with the process?traceability 81% 19% 52%43% 48%57% (7) Is the company connected to automated production systems? 29% 71% (6) Is there a need for real-time data collection? 71% 29% 57% 43% (4)(5) PerformIsuntil there the any efficientsale kind of the handlingof products?control4.1.1. including to guarant Does theexeepiration Companythe transport, date, Have temperatures, storage an Organized and exhibition etc.? Information 67% System? (Network, Servers,33% (10)(9)(8)(7) TheDoesofAre Isproduction thecompanyadvanced the company company cross-checksinformation?control connected perform systems to the data automated necessary?results analysis of production these during analyses systems?the production with the traceabilityprocess? 52%81% 48%19%

43% 57% (7) Is the company connected to automated production systems? 29% 71% (6) Is there a need for real-timeConnectivity)? data collection? 71%57% 29%43% (5) Isuntil there the any sale kind of the of products?control4.1.1. to guarant Does theee Companythe transport, Have storage an Organized and exhibition Information System? (Network, Servers, (10)(9) ofTheDoes production company the company information?cross-checks perform the data results analysis of these during analyses the production with the traceabilityprocess? 52% 48% (8) Are advanced control systems necessary? 81% 19% 43% 57% (7) Is the company connected to automated production systems? 29% 71% (6) Is there a need for real-timeConnectivity)? dataIn Tablecollection? 5, item 1 indicates that just over half of the companies71% in the agro-food sector29% 4.1.1. Does the Company Have an Organized Information57% System? (Network, Servers,43% until the sale of the products? of production information? (9)(8)(10)(8) DoesAreTheAre advancedcompany the advanced company cross-checkscontrol control perform systemsthat thedata necessary?were necessary?results analysis part of ofthese during the analysesinquiry the production processwith the have process?traceability an organized 81% information system, whether19% it Connectivity)? 43% 57% (7) Is the company connected to automated production systems? 29% 71% (6) Is there a need for real-time dataIn Tablecollection? 5, item 1 indicates that just over half of the 71%companies in the agro-food sector29% 4.1.1. Does the Company Have an Organized Information57% System? (Network, Servers,43% of production information? (10)(9)(8) TheDoesAre advancedcompany the company cross-checkscontrol perform systemsconsistsConnectivity)?that the data were Innecessary?results analysisTable of part a dataof 5, of these item during network,the 1analyses inquiry indicates the servers,production processwith that theor just haveeven traceabilityprocess? over coan halfnnectivity. organized of the 29%81%43%companies Atinformation this point, in the system, there agro-food is whethera need sector71%57%19% for it (7) Is the company connected to automated production systems? 4.1.1. Does the Company Have an Organized Information57% System? (Network, Servers,43% the development of information and communication technology and implementation (10)(9)(8)(9) ofTheDoesAre Doesproduction advancedcompany the the company company cross-checksinformation?control perform perform systemsconsistsConnectivity)?that thedatadata wereInnecessary?results analysis Tableanalysis of part a ofdata 5, during ofthese item during network,the 1 theanalyses inquiryindicates the production productionservers, processwith that process? the orjust haveeven traceabilityprocess? over coan halfnnectivity. organized of the 43%companies Atinformation this point, in the system, there agro-food is whethera need sector57% for it 81% 19% strategies4.1.1. Does in the companies Company in Have this sector. an Organized Information57% System? (Network, Servers,43% theconsists development of a data network,of information servers, and or evencommunication connectivity. technology At this point, and there implementation is a need for (10)(9) TheDoesof production company the company cross-checksinformation? performthat the data were Inresults analysisTable part of 5, of these itemduring the 1 analysesinquiry indicates the production processwith that the just have traceabilityprocess? over an half organized of the 81%companies information in the system, agro-food whether sector19% it 4.1.1.strategiesConnectivity)? Does in the companies Company in Have this sector. an Organized Information57% System? (Network, Servers,43% consiststhe development of a data network,of information servers, and or even communication connectivity. technology At this point, and there implementation is a need for (10)(10) Theof Theproduction company company cross-checksinformation? cross-checks4.1.2.that thethe resultswere resultsDoes part ofthe of these Companyofthese the analyses analyses inquiry Use with Planningprocesswith the traceabilitythe have traceabilityand anDecision of organized Support information Tools? system, whether it Connectivity)?strategiesIn Table in companies 5, item 1 indicates in this sector. that just over half of the 57%companies in the agro-food sector43% production information? 4.1.1.the development Does the Company of information Have an Organizedand communication Information technology System? (Network, and implementation Servers, of production information?4.1.2.consiststhat were Does of part athe data Companyof network,the inquiry Use servers, Planningprocess or haveeven and ancoDecisionnnectivity. organized Support Atinformation this Tools? point, system, there is whethera need for it 4.1.1.Connectivity)?strategiesthe developmentIn Does Table in the companies 5, Company item of 1 informationindicates in Have this sector. anthat Organizedand just communication over half Information of the companiestechnology System? in(Network, and the agro-foodimplementation Servers, sector 4.1.2.consists Does of athe data Company network, Use servers, Planning or even and coDecisionnnectivity. Support At this Tools? point, there is a need for thatConnectivity)? were part of the inquiry process have an organized information system, whether it 4.1.1.strategiesthe developmentIn Does Table in the companies 5, Company item of 1 information indicates in Have this sector. anthat Organizedand just communication over half Information of the companiestechnology System? in(Network, and the agro-foodimplementation Servers, sector consiststhat4.1.2. were Does of part athe data Companyof network,the inquiry Use servers, Planningprocess or haveeven and ancoDecisionnnectivity. organized Support Atinformation this Tools? point, system, there is whethera need for it Connectivity)?strategies4.1.1.In Does Table in the companies 5, Companyitem 1 indicates in Have this sector. that an Organized just over half Information of the companies System? in (Network, the agro-food Servers, sector theconsists4.1.2. development Does of athe data Company network,of information Use servers, Planning and or even communicationand coDecisionnnectivity. Support technology At this Tools? point, and there implementation is a need for thatConnectivity)? wereIn Table part 5, ofitem the 1 inquiryindicates process that just have over an half organized of the companies information in the system, agro-food whether sector it strategiesthe development in companies of information in this sector. and communication technology and implementation consiststhat4.1.2. wereIn Does Table of part athe data5, itemCompanyof network,the 1 indicatesinquiry Use servers, processPlanning that justor haveeven overand ancoDecision halfnnectivity. organized of the Support companies Atinformation this Tools? point, in the system, there agro-food is whethera need sector for it thestrategies development in companies of information in this sector. and communication technology and implementation 4.1.2.consiststhat were Does of part athe data Company of network, the inquiry Use servers, processPlanning or haveeven and ancoDecisionnnectivity. organized Support At information this Tools? point, system, there is whethera need for it thestrategiesconsists development of in a companies data of network, information in this servers, sector. and or communication even connectivity. technology At this point,and implementation there is a need 4.1.2. Does the Company Use Planning and Decision Support Tools? strategiesfor the development in companies of informationin this sector. and communication technology and implementation 4.1.2.strategies Does in the companies Company in Use this Planning sector. and Decision Support Tools? 4.1.2. Does the Company Use Planning and Decision Support Tools? 4.1.2. Does the Company Use Planning and Decision Support Tools? In Table5, item 2 indicates the use of planning and decision support tools. A percentage of companies (over 60%) indicated that they do not use any decision support tools. Nowadays, there is a set of computational tools and decision support information aimed at improving processes and activities in companies, which can enable cost reduction with raw material acquisition, storage, logistics, up to the deﬁnition of a price depending on a set of factors associated with production and planning. All these characteristics allow companies to have greater soundness in decisions. In general, companies that answered afﬁrmatively to this question indicated that they make use of a company resource planning software, which is essentially an enterprise resource planning (ERP). In general terms, an ERP system is a software platform developed to integrate various departments of a company, enabling Appl. Sci. 2021, 11, 3454 11 of 18

the automation and storage of all business information, that is, the ERP system enables a unique, continuous and consistent ﬂow of information. Data integration can follow a functional approach, e.g., integrating ﬁnance, accounting, human resources, manufacturing, marketing, sales, purchasing systems, among others, and from a systemic perspective, incorporating transaction processing systems, management information systems, decision support systems, etc.

4.1.3. Does the Company Record the Relationship between the Different Items or Batches Used as Raw Materials and Used Items or Batches of Finished Products, through Computers? In Table5, item 3 shows whether the companies surveyed record, and how, the relationship between different items or lots used as raw materials and used ﬁnished items or lots. About 70% made this registration using a computer.

4.1.4. Perform Efficient Handling Including Expiration Date, Temperatures, etc.? In Table5, item 4 shows the proportion of companies surveyed that performs efficient handling, including expiration date, temperatures, among other parameters. In this case, 67% of companies indicated performing efficient handling at this level. However, only 20% of the companies that responded affirmatively indicated that this process was carried out for the entire chain, using computer systems supported by human resources. The remaining affirmative answers indicated that this process was carried out in its entirety manually.

4.1.5. Is There Any Kind of Control to Guarantee the Transport, Storage and Exhibition Until the Sale of the Products? In Table5, item 5 analyzes the traceability of products, i.e., if there is any type of control to ensure transportation, storage and exposure until the sale of the products is performed. Just over half of the companies surveyed answered in the afﬁrmative (52%) this issue shows the need for sophistication on the part of these companies to carry out traceability throughout the product chain, ensuring the maintenance of organoleptic characteristics, in addition to undeniable food safety. The only control carried out by the companies that responded in the afﬁrmative was temperature control.

4.1.6. Is There a Need for Real-Time Data Collection? This issue, closely linked to the capabilities of companies to know in real time how different activities are unfolding along the product chain, from production, storage for sale, infers the need for real-time data collection. This will take a set of sensors, communication systems and data acquisition and processing. In Table5, item 6 shows this need, and about 70% responded afﬁrmatively. These same companies indicated that the parameter which requires real-time data collection was temperature.

4.1.7. Is the Company Connected to Automated Production Systems? This issue is related to the previous one. In Table5, item 7 shows this need, to which about 70% answer afﬁrmatively. These same companies indicated that the parameter which required real-time data collection was temperature.

4.1.8. Are Advanced Control Systems Necessary? In Table5, item 8 shows the need for advanced control systems for production activities for the companies surveyed. Only 43% of companies answered this question in the afﬁrmative, indicating that these systems are intended for granular control of costs and production.

4.1.9. Does the Company Perform Data Analysis during the Production Process? In order to evaluate the sophistication of management of the production process, this question aimed to analyze the appetite of companies to perform data analysis during the Appl. Sci. 2021, 11, 3454 12 of 18

production process. As shown in Table5, item 9, 81% of the companies stated that they performed data analysis during the production process.

4.1.10. Should the Results of These Analyzes Be Cross-Checked with the Traceability of Production Information? Following questions to assess sophistication, companies were asked whether they cross-referenced the analysis of collected data results during the production process with the traceability of production information. In this case, 57% of companies claimed to carry out this task, as shown in Table5, item 10.

4.2. Phase 2: Assess Real Scenario for IoT Opportunities and Solutions Implementation Aiming to provide IoT solutions, this second phase survey of opportunities was carried out by contacting five selected companies, based on an analysis of the first questionnaire: Delta Cafés, Massimo Zanetti Beverage Iberia, Fumeiros da Guarda, Sabores da Guarda and Claro’s Beekeeping. The choice was made to precisely describe agro-food companies from Portugal. Thus, companies from different segments and maturity stages were chosen. According to this analysis, it was observed that the adaptability rate may take longer due to the complexity of the technology to be implemented. To this end, a model of identification of opportunities was designed according to each company. Table6 describes the mains features of companies, such as designation, sector of activity, awareness of IoT, sector of major investment in company, potential for IoT implementation and expected time for IoT implementation. In this manner, this table reveals an overview of agro-food business in Portugal. Notice that all companies interviewed were aware of IoT technology. Most of them had major investments in production, except Fumeiros da Guarda. All of them had potential to implement IoT solutions. However, some time is necessary to prepare people and installations to receive this technology, only Delta Cafés was ready to receive it immediately. Table7 shows the main advantages of implementation of IoT solutions in each company. Better relationships with customers was expected by all companies, except for Claro’s Beekeeping. Fumeiros da Guarda e Sabores da Soalheira expected increase of food safety with better controls. Delta Cafés expected efficiency in technical assistance, anticipation of problems, to speed up maintenance, cutting downtimes, etc. Massimo Zanetti Beverage Iberia just expected monitoring of work status and Claro’s Beekeeping was interested in an increase in productivity, with better monitoring, controls and, also, alarms that can inform possible problems.

Table 6. Main features of agro-food companies of Portugal.

Awareness Sector of Major Time for Companies Sector Potential for IoT about IoT Investments Implementation Delta Cafés Coffee Yes Production Yes Now Massimo Zanetti Coffee Yes Production Yes 6 to 12 months Beverage Iberia Fumeiros da Meat (cured Prospecting and Yes Yes Not informed Guarda sausages) maintenance Sabores da Guarda Dairy Yes Production Yes Not informed Claro’s Beekeeping Honey Yes Production Yes Not informed Appl. Sci. 2021, 11, 3454 13 of 18

Table 7. Advantages of IoT solutions implementation according to each company.

Companies Advantages More efficiency in technical assistance, anticipation of problems, speed up maintenance, Delta Cafés cutting downtimes, etc. Better relationships with customers. More efficiency in technical assistance, anticipation of problems, speed up maintenance, cutting downtimes, etc. Massimo Zanetti Beverage Iberia Better relationships with customers. Better forecasts. Increase in food safety. Fumeiros da Guarda Better customer relationships, promoting more business. Improvement in product quality, avoiding machinery faults. Better control and warranty of food safety. Sabores da Soalheira Better customer relationships, promoting more business reducing logistic difficulties. Quick detection of problems. Avoid unnecessary displacements. Claro’s Beekeeping Detection of productivity levels. Allows for the definition of the best maintenance schedules for hives. Pattern detection can assist the beekeeper in more active management of the hive.

5. Suggestions and Recommendations Suggestions and recommendations are provided for the digitalization of agro-food companies, based on an analysis of the results of the surveys applied to the sample of companies in the agro-food sector in the central region of the country. Note that the number of companies that have a high level of sophistication relating to the use of information and communication technologies, information systems, decision support systems, control system, regulation, command and measurement of production processes, is still reduced. Table8 shows IoT opportunities for each company, as well as each speciﬁc requirement for IoT application. The opportunities are directly linked to the needs of each company, due to internal processes which can be improve with IoT solutions. The requirements are linked to the speciﬁc reality of company, with their strengths and weakness. All IoT opportunities or solutions are related to monitoring and data register, and also, access data as graphs in order to analyze them. Only Claro’s Beekeeping was interested in threshold alarms to inform the company about possible problems. Basic requirements for all companies were related to preparation of people and installations to receive this technology. Deployment, tests, procedures, training, and maintenance are also a general concern. Figure4 shows a critical analysis of the level of sophistication in the sample of agro- food companies surveyed. Given the complete and cross-examination of the results of the survey, it was found that half of the companies had a zero level of sophistication, while 15% of the companies had a low level. Only 10% of the companies analyzed currently have a high level of sophistication.

Figure 4. Sophistication level of companies in central region of Portugal. Appl. Sci. 2021, 11, 3454 14 of 18

Table 8. Opportunities and requirements for the implementation of IoT according to each company.

Companies IoT Opportunities Requirements

• Team assignment for IoT, departments, Monitoring working status, pressure and responsibilities, procedure training, etc. temperature of production machinery spread • Compatibility and requirements for current Delta Cafés around the world, accessing reports and information technology. graphs easily. • Deployment, tests, procedures, training, maintenance, etc.

• Team assignment for IoT, departments, responsibilities, procedures training, etc. Monitoring working status (working or nor Massimo Zanetti • Compatibility and requirements for current working) of machinery spread around the Beverage Iberia information technology. world, accessing reports and graphs easily. • Deployment, tests, procedures, training, maintenance, etc.

• Identify the correct places to install sensors. • Team assignment for IoT, departments, responsibilities, procedures training, etc. Monitoring temperature of refrigerators, Fumeiros da Guarda • Compatibility and requirements for current accessing reports and graphs easily. information technology. • Deployment, tests, procedures, training, maintenance, etc.

• Team assignment for IoT, departments, responsibilities, procedures training, etc. Monitoring temperatures of milk transported • Compatibility and requirements for current Sabores da Guarda by specialized vehicles. Additionally, information technology. accessing reports and graphs easily. • Deployment, tests, procedures, training, maintenance, etc.

• Speciﬁcation of temperature, humidity and weight sensors. Monitoring temperatures and humidity with • Team assignment for IoT, departments, automatic alarm for speciﬁcs thresholds. responsibilities, procedures training, etc. Claro’s Beekeeping Measure and analysis of each hive’s weigh. • Compatibility and requirements for current Additionally, accessing reports and graphs information technology. easily. • Deployment, tests, procedures, training, maintenance, etc.

Therefore, based on this survey, there is an urgent need to increase the sophistication of agro-food companies in terms of information and communication technologies, information systems and decision support systems. The aim of contributing to the improvement of information management processes with subsequent gains in production, quality, reduction of waste, response time, result in an increase in competitiveness. Thus, the suggestions and recommendations identifying opportunities for improvement originated by this analysis are transversal to all ranks, and are summarized as: • Promote the updating of systems, in order to consider an internal network, which enhances the organization in the face of corporate e-mail and ease of communication via the Internet between employees of the company; • Promote frequent use of ﬁnancial management tools, not just billing software; • Promote the use of customer relationship management (CRM); • Promote the use of integrated enterprise resource planning (ERP); Appl. Sci. 2021, 11, 3454 15 of 18

• Promote the use of information and communications technology (ICT) tools in quality management-oriented processes; • Promote the use of ICT tools in product traceability, monitoring of the company’s productive activities, monitoring energy consumption; • Promote the use of decision support tools in different areas of the company. These results are important to understand and highlight the potential of IoT implementation in the sample of agro-food MSMEs that can be extended to the country scale. Additionally, the next section will discuss possible opportunities and solutions for such a niche.

6. Conclusions Population growth is creating more demand and putting pressure on agro-industry. The food demand forecast is estimated 60% more by 2050. Due to this challenging scenario, the UN and EU share concerns about how scarce resources are to be managed, in terms of food loss and waste, land, water, energy, emissions, and so on. The European Commission is working on a Green Deal in order to reduce emissions. Thus, initial commitments could become laws and obligations, pushing companies to adapt and be more eco-efficient. IoT is a technology that can revolutionize agro-food business, in terms of efficiency, mitigating challenges like monitoring, controlling and tracking of crops and animals on farms, and allowing precision agriculture. Additionally, changing old concepts of farming to new ones, like Agriculture 4.0 or smart farming, where data are collected in real-time and processed using optimization algorithms of artificial intelligence based in data-driven decisions and other technologies, aiming to optimize production results. This survey assesses the potential implementation of IoT technology. It was applied to 21 agro-food companies, belonging to the milk, honey, olive oil, jams, fruticulture, bakery and pastry, meat, coffee, and wine sectors, which are located in the central region of Portugal. Additionally, this study helps, on basis of company characterizations, to propose actions and measures that promote the development, economic growth, employment by increasing competitiveness in the economy and traditional sectors. The analysis of results for the first stage points to a low level of sophistication, which means low maturity for IoT implementation. However, it also indicates the possibility of enormous potential for efficiency growth by applying IoT solutions. Efforts need to be made to transfer knowledge to farmers, unlocking the potential they already have, but in many cases remains hidden, not measured, not processed or even just ignored, caused by a lack of information. Deeper analyses were performed in a second survey stage, with of five companies, to assess a real scenario of IoT implementation. This approach revealed many opportunities for IoT solutions, mainly for monitoring and measuring variables of production that can possibly lead to better decisions by managers. Further, the results highlight the constraints at human resources and facilities levels that cannot receive the technology now, and need at least 6 months until 2 years to start any deployment. In general, there is a great potential for implementation of IoT in Portugal, but also great challenges. to The lack of knowledge related to IoT technologies by the company’s human resources is highlighted. This condition can be mitigate by knowledge transfer and training, Maturity of sophistication is another concern, since installations are the basis to receive new technology. Thus, suggestions and recommendations identifying opportunities for improvement that can be started right now are: renew or install communications systems, use of CRM and ERP, use of financial tools, use of ICT tools to allow traceability, monitoring of a company’s productive activities, monitoring energy consumption and the use of decision support tools in different areas. Future research work will include a larger sample of companies in order to improve characterization, generalization and representativeness of Portuguese agro-industry MSMEs. Appl. Sci. 2021, 11, 3454 16 of 18

Author Contributions: Conceptualization, H.S., V.N.G.J.S. and J.M.L.P.C.; methodology, H.S., V.N.G.J.S. and J.M.L.P.C.; validation, H.S., V.N.G.J.S. and J.M.L.P.C.; formal analysis, P.D.G.; in- vestigation, H.S., V.N.G.J.S. and J.M.L.P.C.; resources, H.S.; data curation, P.D.G.; writing—original draft preparation, C.M.F.; writing—review and editing, P.D.G.; supervision, P.D.G.; project adminis- tration, H.S.; funding acquisition, H.S. All authors have read and agreed to the published version of the manuscript. Funding: This study is within the activities of project IOTEC—Development of Technological Capa- bilities in the Industrial Application of the Internet of Things (Code: 0123_IOTEC_3_E), funded by the European Regional Development Fund (ERDF) within the framework of the Interreg program V-A Spain-Portugal 2014–2020 (PocTep). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Acknowledgments: P.D.G. acknowledges Fundação para a Ciência e a Tecnologia (FCT—MCTES) for its financial support via the project UIDB/00151/2020 (C-MAST). V.N.G.J.S. and J.M.L.P.C. acknowledge that this work is funded by FCT/MCTES through national funds and when applicable co-funded EU funds under the project UIDB/50008/2020. The authors would like to acknowledge the company InspiringSci, Lda for the interest and valuable contribution to the successful development of this work. Conflicts of Interest: The authors declare no conflict of interest.

References 1. Spang, E.S.; Moreno, L.C.; Pace, S.A.; Achmon, Y.; Donis-Gonzalez, I.; Gosliner, W.A.; Jablonski-Shefﬁeld, M.P.; Abdul Momin, M.; Quested, T.E.; Winans, K.S.; et al. Food Loss and Waste: Measurement, Drivers, and Solutions. Annu. Rev. Environ. Resour. 2019, 44, 117–156. [CrossRef] 2. FAO. The State of Food and Agriculture 2020; Food and Agriculture Organization of the United Nations (FAO): Rome, Italy, 2020; ISBN 978-92-5-133441-6. 3. Acosta-Alba, I.; Chia, E.; Andrieu, N. The LCA4CSA framework: Using life cycle assessment to strengthen environmental sustainability analysis of climate smart agriculture options at farm and crop system levels. Agric. Syst. 2019, 171, 155–170. [CrossRef] 4. Akhigbe, B.I.; Munir, K.; Akinade, O.; Akanbi, L.; Oyedele, L.O. IoT Technologies for Livestock Management: A Review of Present Status, Opportunities, and Future Trends. Big Data Cogn. Comput. 2021, 5, 10. [CrossRef] 5. United Nations. The Sustainable Development Goals Report 2020; Department of Economic and Social Affairs: New York, NY, USA, 2020; ISBN 978-92-1-101425-9. 6. European Commission A European Green Deal | European Commission. Available online: https://ec.europa.eu/info/strategy/ priorities-2019-2024/european-green-deal_en (accessed on 5 March 2021). 7. European Commission Regulation of the European Parliament and of the Council. Available online: https://eur-lex.europa.eu/ legal-content/EN/TXT/?qid=1588581905912&uri=CELEX:52020PC0080 (accessed on 6 March 2021). 8. European Commission. European Union—Agriculture and Rural Development. Statistical Factsheet 2020; European Commission, European Union: Luxembourg, 2020. 9. Weersink, A.; Fraser, E.; Pannell, D.; Duncan, E.; Rotz, S. Opportunities and Challenges for Big Data in Agricultural and Environmental Analysis. Annu. Rev. Resour. Econ. 2018, 10, 19–37. [CrossRef] 10. Grogan, A. Smart farming. Eng. Technol. 2012, 7, 38. [CrossRef] 11. Farooq, M.S.; Riaz, S.; Abid, A.; Umer, T.; Zikria, Y. Bin Role of IoT Technology in Agriculture: A Systematic Literature Review. Electronics 2020, 9, 319. [CrossRef] 12. Romeo, L.; Petitti, A.; Marani, R.; Milella, A. Internet of Robotic Things in Smart Domains: Applications and Challenges. Sensors 2020, 20, 3355. [CrossRef][PubMed] 13. Debauche, O.; Trani, J.; Mahmoudi, S.; Manneback, P.; Bindelle, J.; Mahmoudi, S.; Lebeau, F. Data Management and Internet of Things: A Methodological Review in Smart Farming. Internet Things 2021, 100378. [CrossRef] 14. Gonzalez-de-Santos, P.; Fernández, R.; Sepúlveda, D.; Navas, E.; Emmi, L.; Armada, M. Field Robots for Intelligent Farms— Inhering Features from Industry. Agronomy 2020, 10, 1638. [CrossRef] 15. Tsouros, D.C.; Bibi, S.; Sarigiannidis, P.G. A Review on UAV-Based Applications for Precision Agriculture. Information 2019, 10, 349. [CrossRef] 16. Ullah, Z.; Al-Turjman, F.; Moatasim, U.; Mostarda, L.; Gagliardi, R. UAVs joint optimization problems and machine learning to improve the 5G and Beyond communication. Comput. Netw. 2020, 182, 107478. [CrossRef] Appl. Sci. 2021, 11, 3454 17 of 18

17. Escamilla-García, A.; Soto-Zarazúa, G.M.; Toledano-Ayala, M.; Rivas-Araiza, E.; Gastélum-Barrios, A. Applications of Artificial Neural Networks in Greenhouse Technology and Overview for Smart Agriculture Development. Appl. Sci. 2020, 10, 3835. [CrossRef] 18. Jha, K.; Doshi, A.; Patel, P.; Shah, M. A comprehensive review on automation in agriculture using artificial intelligence. Artif. Intell. Agric. 2019, 2, 1–12. [CrossRef] 19. Cardim Ferreira Lima, M.; Damascena de Almeida Leandro, M.E.; Valero, C.; Pereira Coronel, L.C.; Gonçalves Bazzo, C.O. Automatic Detection and Monitoring of Insect Pests—A Review. Agriculture 2020, 10, 161. [CrossRef] 20. Wolfert, S.; Ge, L.; Verdouw, C.; Bogaardt, M. Big Data in Smart Farming—A review. Agric. Syst. 2017, 153, 69–80. [CrossRef] 21. Newton, J.E.; Nettle, R.; Pryce, J.E. Farming smarter with big data: Insights from the case of Australia’s national dairy herd milk recording scheme. Agric. Syst. 2020, 181, 102811. [CrossRef] 22. Torky, M.; Hassanein, A.E. Integrating blockchain and the internet of things in precision agriculture: Analysis, opportunities, and challenges. Comput. Electron. Agric. 2020, 178, 105476. [CrossRef] 23. Niknejad, N.; Ismail, W.; Bahari, M.; Hendradi, R.; Salleh, A.Z. Mapping the research trends on blockchain technology in food and agriculture industry: A bibliometric analysis. Env. Technol. Innov. 2021, 21, 101272. [CrossRef] 24. Ampatzidis, Y.; De Bellis, L.; Luvisi, A. iPathology: Robotic Applications and Management of Plants and Plant Diseases. Sustainability 2017, 9, 1010. [CrossRef] 25. Khanna, A.; Kaur, S. Evolution of Internet of Things (IoT) and its significant impact in the field of Precision Agriculture. Comput. Electron. Agric. 2019, 157, 218–231. [CrossRef] 26. Gaspar, P.D.; Caldeira, J.M.L.P.; Soares, V.N.G.J. ICT-enabled agri-food systems. Chapter 11. In Environment and Climate-Smart Food Production; Galanakis, C.M., Ed.; Springer International Publishing: Cham, Switzerland, 2021; ISBN 978-3-030-71570-0. [CrossRef] 27. Gaspar, P.D.; Soares, V.N.G.J.; Caldeira, J.M.L.P.; Andrade, L.P.; Soares, C.D. Technological modernization and innovation of traditional agri-food companies based on ICT solutions–the Portuguese case study. J. Food Process. Preserv. 2019, e14271. [CrossRef] 28. Silva, J.; Fontes, R.; Caldeira, J.M.L.P.; Soares, V.N.G.J.; Gaspar, P.D. MobiSensA: Development of a mobile APP for iSensA platform. In Proceedings of the 13th Iberian Conference on Information Systems and Technologies (CISTI’2018), Caceres, Spain, 13–16 June 2018. 29. Caldeira, J.M.L.P.; Soares, V.N.G.J.; Gaspar, P.D.; Rodrigues, J.J.P.C.; Fontes, R. iSensA—A system for collecting and integrating sensor data. Adv. Sci. Technol. Eng. Syst. J. 2018, 3, 213–221. [CrossRef] 30. Gaspar, P.D.; Soares, V.N.G.J.; Caldeira, J.M.L.P.; Andrade, L.P.; Domingues, C. Potential for technological modernisation and innovation based on ICT in agri-food companies of central region of Portugal. J. Adv. Agric. Technol. 2015, 2, 75–82. [CrossRef] 31. Varandas, L.; Faria, J.; Gaspar, P.D.; Aguiar, M.L. Low-Cost IoT Remote Sensor Mesh for Large-Scale Orchard Monitorization. J. Sens. Actuator Netw. 2020, 9, 44. [CrossRef] 32. Marcu, I.; Suciu, G.; Bălăceanu, C.; Vulpe, A.; Drăgulinescu, A.-M. Arrowhead Technology for Digitalization and Automation Solution: Smart Cities and Smart Agriculture. Sensors 2020, 20, 1464. [CrossRef][PubMed] 33. Hajjaji, Y.; Boulila, W.; Farah, I.R.; Romdhani, I.; Hussain, A. Big data and IoT-based applications in smart environments: A systematic review. Comput. Sci. Rev. 2021, 39, 100318. [CrossRef] 34. Verdouw, C.; Tekinerdogan, B.; Beulens, A.; Wolfert, S. Digital twins in smart farming. Agric. Syst. 2021, 189, 103046. [CrossRef] 35. Descheemaeker, K.; Zijlstra, M.; Masikati, P.; Crespo, O.; Homann-Kee Tui, S. Effects of climate change and adaptation on the livestock component of mixed farming systems: A modelling study from semi-arid Zimbabwe. Agric. Syst. 2018, 159, 282–295. [CrossRef] 36. Talavera, J.M.; Tobón, L.E.; Gómez, J.A.; Culman, M.A.; Aranda, J.M.; Parra, D.T.; Quiroz, L.A.; Hoyos, A.; Garreta, L.E. Review of IoT applications in agro-industrial and environmental fields. Comput. Electron. Agric. 2017, 142, 283–297. [CrossRef] 37. Ratnaparkhi, S.; Khan, S.; Arya, C.; Khapre, S.; Singh, P.; Diwakar, M.; Shankar, A. Smart agriculture sensors in IOT: A review. Mater. Today Proc. 2020.[CrossRef] 38. Shafi, U.; Mumtaz, R.; García-Nieto, J.; Hassan, S.A.; Zaidi, S.A.R.; Iqbal, N. Precision Agriculture Techniques and Practices: From Considerations to Applications. Sensors 2019, 19, 3796. [CrossRef] 39. Boursianis, A.D.; Papadopoulou, M.S.; Diamantoulakis, P.; Liopa-Tsakalidi, A.; Barouchas, P.; Salahas, G.; Karagiannidis, G.; Wan, S.; Goudos, S.K. Internet of Things (IoT) and Agricultural Unmanned Aerial Vehicles (UAVs) in smart farming: A comprehensive review. Internet Things 2020, 100187. [CrossRef] 40. Buja, I.; Sabella, E.; Monteduro, A.G.; Chiriacò, M.S.; De Bellis, L.; Luvisi, A.; Maruccio, G. Advances in Plant Disease Detection and Monitoring: From Traditional Assays to In-Field Diagnostics. Sensors 2021, 21, 2129. [CrossRef][PubMed] 41. Al-Turjman, F. The road towards plant phenotyping via WSNs: An overview. Comput. Electron. Agric. 2019, 161, 4–13. [CrossRef] 42. Sharma, R.; Kamble, S.S.; Gunasekaran, A. Big GIS analytics framework for agriculture supply chains: A literature review identifying the current trends and future perspectives. Comput. Electron. Agric. 2018, 155, 103–120. [CrossRef] 43. Morais, R.; Silva, N.; Mendes, J.; Adão, T.; Pádua, L.; López-Riquelme, J.A.; Pavón-Pulido, N.; Sousa, J.J.; Peres, E. mySense: A comprehensive data management environment to improve precision agriculture practices. Comput. Electron. Agric. 2019, 162, 882–894. [CrossRef] Appl. Sci. 2021, 11, 3454 18 of 18

44. Sishodia, R.P.; Ray, R.L.; Singh, S.K. Applications of Remote Sensing in Precision Agriculture: A Review. Remote Sens. 2020, 12, 3136. [CrossRef] 45. Müller, P.; Schmid, M. Intelligent packaging in the food sector: A brief overview. Foods 2019, 8, 16. [CrossRef][PubMed] 46. Antony, A.P.; Leith, K.; Jolley, C.; Lu, J.; Sweeney, D.J. A Review of Practice and Implementation of the Internet of Things (IoT) for Smallholder Agriculture. Sustainability 2020, 12, 3750. [CrossRef] 47. IOTEC O Projeto | IOTEC. Available online: https://iotec.usal.es/pt/o-projeto (accessed on 2 March 2021). 48. InovCluster. Available online: https://www.inovcluster.pt/# (accessed on 9 March 2021).