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Technological University Dublin ARROW@TU Dublin Doctoral Theses&Dissertations 2020-11-30 Dublin Smart City Data Integration, Analysis and Visualisation Hammad Ul Ahad Technological University Dublin Follow this and additional works at: https://arrow.tudublin.ie/ittthedoc Part of the Computer Sciences Commons Recommended Citation Ul Ahad, H. (2020). Dublin Smart City Data Integration, Analysis and Visualisation. Dissertation. Technological University Dublin. doi:10.21427/5ekz-6d18 This Theses, Masters is brought to you for free and open access by the Theses&Dissertations at ARROW@TU Dublin. It has been accepted for inclusion in Doctoral by an authorized administrator of ARROW@TU Dublin. For more information, please contact [email protected], [email protected]. This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License Dublin Smart City Data Integration, Analysis and Visualisation A Thesis Presented For the Award of Masters by Research by Hammad Ul Ahad Technological University Dublin – Tallaght Campus Department of Computer Science For Research Carried Out Under the Guidance of Dr. Martin O’Connor Dr. John Burns Submitted to Technological University Dublin December 2020 Declaration I hereby certify that the material, which I now submit for assessment on the program of study leading to the award of a Master of Science (research), is entirely my own work and has not been taken from the work of others except to the extent that such work has been cited and acknowledged with in the text of my own work. No portion of the work contained in this thesis has been submitted in support of an application for another degree or qualification to this or any other institution. Signature of candidate Date I/We hereby certify that to the best of my knowledge all the unreferenced work described in this thesis and submitted for the award of a Master of Science (research) is entirely the work of Hammad Ul Ahad. No portion of the work contained in this thesis has been submitted in support of an application for another degree or qualification to this or any other institution. Signature of supervisor Date Signature of supervisor Date Hammad Ul Ahad December 2020 Acknowledgements In the name of ALLAH the most gracious and the most merciful. All praises and glory to the almighty ALLAH, who gave me the strength and courage to complete this task, peace and blessings be upon Prophet MUHAMMAD. I would like to express my gratitude to my principal supervisor Dr. Martin O’Connor (TU Dublin, Tallaght) for his careful guidance, tremendous patience, remarks, and eagerness to provide support throughout the learning process and for providing me a convenient direction to complete my research project. He gave me the opportunity to gain valuable skills by working on this project and encouraged me in sharpening my technical skills. He provided me consistent support in the face of uncertainty at any stage of my work on the thesis. I would also like to special thanks to my co-supervisor Dr. John Burns (TU Dublin, Tallaght) for his generous feedback, valuable corrections, and provision of the up-to-date information. I would like to special thanks to Dr. Barry Feeney (Head of Computing Department, TU Dublin, Tallaght) for providing me a safe and supportive environment to finish my thesis and get valuable work experience. In addition, I would like to acknowledge the support received from all colleagues, lecturers, and technicians. I want to say to my parents, Zaheer Ullah-(late) and Ishrat Sumayya, that my heart is full of love, respect and deep appreciation for all they gave me, for helping me to become a person I am today, for always being there to give me a hand. I also want to thank them for their ruthless judgments that gave me so much motivation and willingness to learn and grow. My gratitude also goes towards all the members of my family and relatives for all the sacrifices they had made to support me, and for their love and prayers. A very-very special thanks to my parents, specifically to my beloved mother, as without her powerful prayers and support I would not be able to achieve anything in life. vi To my beloved sisters Noor-un-Nisa, Najm-us-Sahar, Kokab Aseela, my younger brother Saad-ul-Samad, my brothers-in-law Alauddin Qureshi, Riaz Ahmed, and Hasnain Ali for their consistent support and prayers. To my beloved aunt Frankie Kelleher, for always looking after me, loving me as her own son, and supporting me all the time. To my close friends Dr. Shahzad Imar and Dr. Abdul Ghaffar for always giving me the best possible advice, constant support, encouragement, and motivating me whenever I am going through difficult situations in life. Abstract Data is an important resource for any organisation, to understand the in-depth working and identifying the unseen trends with in the data. When this data is efficiently processed and analysed it helps the authorities to take appropriate decisions based on the derived insights and knowledge, through these decisions the service quality can be improved and enhance the customer experience. A massive growth in the data generation has been observed since two decades. The significant part of this generated data is generated from the dumb and smart sensors. If this raw data is processed in an efficient manner it could uplift the quality levels towards areas such as data mining, data analytics, business intelligence and data visualisation. The smart city idea is now strongly established, the proper and efficient management of public and private infrastructures will result in improved living standards. The Dublin City local authorities are providing over 200 open source datasets containing the captured data of the daily city life. However, in terms of processing this data there are some challenges available at the moment such as: • The data silos are standalone and isolated in nature. • The data formats in these data silos are also heterogeneous. • There is often a lack of structure and meaningful context in the data. Data Integration methods are used to integrate these heterogeneous data silos and provide users with data as a unified view. There is no automated procedure to integrate these datasets now, the integration step is the key enabler to transform these independent datasets into a smart city repository. The novel aspect of this research is the provision of an on-demand Extract, Load and Transform (ELT) framework that will perform the structural, contextual and augmentation enrichment towards the data streams and will generate the mapping rules between the source and target schema. Also, it will transform and integrate the selected datasets according to the selected facts and dimensions by the domain experts. The primary objectives of the thesis consist in the development of an on-demand Extract, Load and Transform framework using the modern tools that will provide the integration viii services based on the dimensions and measures of the provided data sets and will fulfil the research demands. The designed algorithms for the ELT framework will perform structural, contextual as well as augmentation enrichment towards the provided data streams. In our work we have described our designed Application Programmable Interface (API) query service using the Python programming language. This API service is built to connect our Data Visualisation web application with our canonical data model. A user can communicate with our Dublin smart city repository by using our API service and could connect the API to any web or mobile application in the future. In the framework for visualisation we have developed an analytics web application for Dublin Bikes sharing scheme to demonstrate the new insights and bikes usage patterns, this application is connected to our smart city repository. In addition, based on our observations from the web application we have carried out a detailed analysis on Dublin Bikes data and developed an efficient economical model for Dublin bike sharing scheme and suggested a pairing strategy for replenishing. Table of contents List of figures xv List of tables xvii 1 Introduction1 1.1 Background . .2 1.2 Motivation . .3 1.3 Research Tasks and Objectives . .4 1.4 Subject of Consideration . .5 1.5 Contribution . .5 1.6 Thesis Organisation . .6 2 Literature Review7 2.1 Data Integration Architectures . .7 2.1.1 Cloud-based Integration . .8 2.1.2 Multi-Level Architecture for Smart City . 10 2.1.3 CityPulse Framework . 12 2.1.4 Online Data Integration Process Framework . 13 2.1.5 Domain-Specific Automated ETL Architecture . 15 2.1.6 Automatically Generated Data Marts Architecture . 19 2.2 Bikes Sharing Schemes . 25 2.2.1 Growth of Cycling in Dublin City . 25 2.2.2 Smart Bike Sharing System to make the City Smarter . 27 2.2.3 Visual Analysis of Citi Bike-Sharing System of New York . 28 2.2.4 User Satisfaction Based Model for Resource Allocation in Bike- Sharing Systems . 31 2.3 Summary . 34 x Table of contents 3 Extract, Load and Transform (ELT) Framework 37 3.1 Experimental Setup . 37 3.2 Methodology and Architecture . 37 3.3 Dublin Public Transport Infrastructures . 40 3.3.1 Dublin Bus Infrastructure . 41 3.3.2 Dublin Bikes Infrastructure . 50 3.3.3 Dublin Luas Infrastructure . 56 3.3.4 Dublin Motorways Infrastructure . 63 3.3.5 Dublin Environment Infrastructure . 69 3.4 Summary . 72 4 Query and Visualisation Service 75 4.1 Experimental Setup . 75 4.2 Application Programmable Interface (API) . 75 4.3 Dublin Bikes Sharing Scheme (DBSS) Query Service . 76 4.3.1 DBSS Query Service Response . 76 4.4 Data Visualisation . 77 4.5 Dublin Bikes Peak Times . 78 4.5.1 One day Tab .
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