Abstract
The concept of smart cities is getting popularity day by day. Many countries have started adopting the idea of smart city to improve the quality of life by achieving the recommended level of sustainable development. The smart city is a technologically advanced area which could understand the world by analyzing the data in order to improve living conditions. The underlying technology infrastructure of smart cities are wireless sensor network (WSN), Internet of thing (IoT), RFID, and 6G are among others. Along with the technology, the role of machine learning and data analytics can’t be ignored. The smart cities generate massive amount of data from the monitoring equipments and sensors. Big data analytics is one of the important technologies which is capable of improving intelligent urban facilities. In smart cities large amount of data is continuously received from many sensors, autonomous machines or intelligent IoT devices. The accurate prediction depends on the approaches of data analytics and machine learning techniques. This chapter presents fundamental of smart cities, vertical in smart cities and data analytics approaches.
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References
United Nations, Department of Economic and Social Affairs. World urbanization prospects: the 2014 revision. New York (2014). https://esa.un.org/unpd/wup/Highlights/WUP2014-Highlights.pdf
Abu-Lughod J, Hay RJ (2013) Third world urbanization. Routledge Kegan & Paul, Abingdon
Mohanty SP, Choppali U, Kougianos E (July 2016)Everything you wanted to know about smart cities: The Internet of things is the backbone. IEEE Consumer Electron Magaz 5(3):60–70. https://doi.org/10.1109/MCE.2016.2556879
Abuhasel KA, Khan MA (2020) A secure industrial Internet of Things (IIoT) framework for resource management in smart manufacturing. IEEE Access 8:117354–117364. https://doi.org/10.1109/ACCESS.2020.3004711
Khan MA, Abuhasel KA (2020) Advanced metameric dimension framework for heterogeneous industrial Internet of things. Comput Intell 1–21. https://doi.org/10.1111/coin.12378
Khan MA, Quasim MT, Alghamdi NS, Khan MY (2020) A secure framework for authentication and encryption using improved ECC for IoT-based medical sensor data. IEEE Access 8:52018–52027. https://doi.org/10.1109/ACCESS.2020.2980739
Khan MA (2020) An IoT framework for heart disease prediction based on MDCNN classifier. IEEE Access 8:34717–34727. https://doi.org/10.1109/ACCESS.2020.2974687
Mardacany E (2014)Smart cities characteristics: importance of buit environments components. In: IET conference on future intelligent cities, London, pp 1–6. https://doi.org/10.1049/ic.2014.0045
Al Nuaimi E, Al Neyadi H, Mohamed N, Al-Jaroodi J (2015) Applications of big data to smart cities. J Internet Serv Appl 6(1):25
Khan Z, Anjum A, Soomro K, Atif Tahir M (2015) Towards cloud based big data analytics for smart future cities. J Cloud Comput 4(1):1-11
Hammad R, Ludlow D (2016) Towards a smart learning environment for smart city governance. In Proceedings of the 9th international conference on utility and cloud computing, pp 185–190
Tabrez Quasim M et al (2019) 5V’s of big data via cloud computing: uses and importance. Sci Int(Lahore) 31(3):367–371
Tabrez Quasim M, Meraj M (2017) Big data security and privacy: a short review. Int J Mech Eng Technol 8(4):408–412. https://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=4
Pramanik MI, Lau RYK, Demirkan H, Abul Kalam Azad M (2017) Smart health: big data enabled health paradigm within smart cities. Expert Syst Appl 87:370–383
Khan MA, Algarni F (2020) A healthcare monitoring system for the diagnosis of heart disease in the IoMT cloud environment using MSSO-ANFIS. IEEE Access 8:122259–122269. https://doi.org/10.1109/ACCESS.2020.3006424
Xiang Z, Fesenmaier DR (2017) Big data analytics, tourism design and smart tourism. In: Analytics in smart tourism design, pp 299–307. Springer, Cham
Bradlow ET, Gangwar M, Kopalle P, Voleti S (2017) The role of big data and predictive analytics in retailing. J Retail 93(1):79–95
Schlieski T, David Johnson B (2012) Entertainment in the age of big data. Proceedings of the IEEE 100, no. Special Centennial Issue (2012): 1404–1408
Wang Z, Wei G, Zhan Y, Sun Y (2017) Big data in telecommunication operators: data, platform and practices. J Commun Inf Netw 2(3):78–91
Lv S (2019) Design of the automobile marketing system based on the big data. In: International conference on big data analytics for cyber-physical-systems, pp 1713–1719. Springer, Singapore
Fang B, Zhang P (2016) Big data in finance. In: Big data concepts, theories, and applications, pp 391-412. Springer, Cham
Yaqoob I, Hashem IAT, Mehmood Y, Gani A, Mokhtar S, Guizani S (2017) Enabling communication technologies for smart cities. IEEE Commun Magaz 55(1): 112–120, January. https://doi.org/10.1109/MCOM.2017.1600232CM
Quasim MT (2015) Artificial intelligence as a business forecasting and error handling tool. COMPUSOFT Int J Adv Comput Technol 4(2), February-2015 (Volume-IV, Issue-II)
Quasim MT, Khan MA, Abdullah M, Meraj M, Singh SP, Johri P (2019) Internet of things for smart healthcare: a hardware perspective. In: 2019 first international conference of intelligent computing and engineering (ICOICE), Hadhramout, Yemen, 2019, pp 1–5. https://doi.org/10.1109/ICOICE48418.2019.9035175
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Quasim, M.T., Khan, M.A., Algarni, F., Alshahrani, M.M. (2021). Fundamentals of Smart Cities. In: Khan, M.A., Algarni, F., Quasim, M.T. (eds) Smart Cities: A Data Analytics Perspective. Lecture Notes in Intelligent Transportation and Infrastructure. Springer, Cham. https://doi.org/10.1007/978-3-030-60922-1_1
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