Abstract
The Smart City is the most complete and covered framework that meets the need of different project facets related to the smart city. It allows the cities to use the urban network and raise their economic power, unique solutions of technology, and build the most efficient systems. Smart City is the advanced developmental product of the smart economy and information technology. It relies upon wireless networking, broadcast networking, internet mesh networking, telecommunication network, and the end-to-end sensor network in which the Internet of Things (IoT) is the core. The IoT serves as the core for integrating the wide variety of sensors in each day's objects and interconnects the sensors through the internet using specific protocols for exchanging the communications and information that lead to location tracking, management, monitoring, and intelligent achievement recognition. It not only supports one city but also interconnects it with the other smart cities. This paper aims to explore the use of IoT-based machine learning approaches that help develop a smart city.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aburayya, A., Alshurideh, M., Al Marzouqi, A., Al Diabat, O., Alfarsi, A., Suson, R., Bash, M., & Salloum, S. A. (2020). An empirical examination of the effect of TQM practices on hospital service quality: An assessment study in uae hospitals. Systematic Reviews in Pharmacy, 11(9). https://doi.org/10.31838/srp.2020.9.51
Ahmed, Z. E., Hasan, M. K., Saeed, R. A., Hassan, R., Islam, S., Mokhtar, R. A., Khan, S., & Akhtaruzzaman, M. (2020). Optimizing energy consumption for cloud internet of things. Frontiers of Physics, 8, 358. https://doi.org/10.3389/Fphy
Akhtar, A., Akhtar, S., Bakhtawar, B., Kashif, A. A., Aziz, N., & Javeid, M. S. (2021). COVID-19 Detection from CBC using Machine Learning Techniques. International Journal of Technology, Innovation and Management (IJTIM), 1(2), 65–78. https://doi.org/10.54489/ijtim.v1i2.22
Akhtaruzzaman, M., Hasan, M. K., Kabir, S. R., Abdullah, S. N. H. S., Sadeq, M. J., & Hossain, E. (2020). HSIC bottleneck based distributed deep learning model for load forecasting in smart grid with a comprehensive survey. IEEE Access.
Al Ali, A. (2021). The impact of information sharing and quality assurance on customer service at uae banking sector. International Journal of Technology, Innovation and Management (IJTIM), 1(1), 01–17. https://doi.org/10.54489/ijtim.v1i1.10.
Al Batayneh, R. M., Taleb, N., Said, R. A., Alshurideh, M. T., Ghazal, T. M., & Alzoubi, H. M. (2021). IT governance framework and smart services integration for future development of Dubai infrastructure utilizing ai and big data, its reflection on the citizens standard of living. The International Conference on Artificial Intelligence and Computer Vision, 235–247.
Al Shebli, K., Said, R. A., Taleb, N., Ghazal, T. M., Alshurideh, M. T., & Alzoubi, H. M. (2021). RTA’s employees’ perceptions toward the efficiency of artificial intelligence and big data utilization in providing smart services to the residents of Dubai. The International Conference on Artificial Intelligence and Computer Vision, 573–585.
AlHamad, A., Alshurideh, M., Alomari, K., Kurdi, B., Alzoubi, H., Hamouche, S., & Al-Hawary, S. (2022). The effect of electronic human resources management on organizational health of telecommuni-cations companies in Jordan. International Journal of Data and Network Science, 6(2), 429–438.
Alhamad, A. Q. M., Akour, I., Alshurideh, M., Al-Hamad, A. Q., Kurdi, B. A., & Alzoubi, H. (2021). Predicting the intention to use google glass: A comparative approach using machine learning models and PLS-SEM. International Journal of Data and Network Science, 5(3). https://doi.org/10.5267/j.ijdns.2021.6.002
Ali, N., Ahmed, A., Anum, L., Ghazal, T. M., Abbas, S., Khan, M. A., Alzoubi, H. M., & Ahmad, M. (2021). Modelling supply chain information collaboration empowered with machine learning technique. Intelligent Automation and Soft Computing, 30(1), 243–257. https://doi.org/10.32604/iasc.2021.018983
Ali, N., M. Ghazal, T., Ahmed, A., Abbas, S., A. Khan, M., Alzoubi, H., Farooq, U., Ahmad, M., & Adnan Khan, M. (2022). Fusion-Based Supply Chain Collaboration Using Machine Learning Techniques. Intelligent Automation & Soft Computing, 31(3), 1671–1687. https://doi.org/10.32604/iasc.2022.019892
Ali, T., Irfan, M., Shaf, A., Saeed Alwadie, A., Sajid, A., Awais, M., & Aamir, M. (2020). A secure communication in IoT enabled underwater and wireless sensor network for smart cities. Sensors, 20(15), 4309.
Aljumah, A., Nuseir, M. T., & Alshurideh, M. T. (2021). The impact of social media marketing communications on consumer response during the COVID-19: Does the brand equity of a university matter. The Effect of Coronavirus Disease (COVID-19) on Business Intelligence, 334, 384–367.
Alnazer, N. N., Alnuaimi, M. A., & Alzoubi, H. M. (2017). Analysing the appropriate cognitive styles and its effect on strategic innovation in Jordanian universities. International Journal of Business Excellence, 13(1), 127–140. https://doi.org/10.1504/IJBEX.2017.085799
Alnuaimi, M., Alzoubi, H. M., Ajelat, D., & Alzoubi, A. A. (2021). Towards intelligent organisations: An empirical investigation of learning orientation’s role in technical innovation. International Journal of Innovation and Learning, 29(2), 207–221. https://doi.org/10.1504/IJIL.2021.112996
Alsharari, N. (2021). Integrating blockchain technology with internet of things to efficiency. International Journal of Technology, Innovation and Management (IJTIM), 1(2), 1–13.
Alshurideh, M. (2022). Does electronic customer relationship management (E-CRM) affect service quality at private hospitals in Jordan? Uncertain Supply Chain Management, 10(2), 1–8.
AlShurideh, M., Alsharari, N. M., & Al Kurdi, B. (2019). Supply chain integration and customer relationship management in the airline logistics. Theoretical Economics Letters, 9(02), 392–414.
Alshurideh, M., Gasaymeh, A., Ahmed, G., Alzoubi, H., & Kurd, B. A. (2020). Loyalty program effectiveness: Theoretical reviews and practical proofs. Uncertain Supply Chain Management, 8(3). https://doi.org/10.5267/j.uscm.2020.2.003
Alshurideh, M. T., Al Kurdi, B., Alzoubi, H. M., Ghazal, T. M., Said, R. A., AlHamad, A. Q., Hamadneh, S., Sahawneh, N., & Al-kassem, A. H. (2022). Fuzzy assisted human resource management for supply chain management issues. Annals of Operations Research, 1–19.
Alshurideh, M. T., Kurdi, B. A., AlHamad, A. Q., Salloum, S. A., Alkurdi, S., Dehghan, A., Abuhashesh, M., & Masa’deh, R. (2021). Factors affecting the use of smart mobile examination platforms by universities’ postgraduate students during the COVID 19 pandemic: An empirical study. Informatics, 8(2), 32.
Alshurideh, M. T., & Shaltoni, A. M. (2014). Marketing communications role in shaping consumer awareness of cause-related marketing campaigns. International Journal of Marketing Studies, 6(2), 163.
Alshurideh, M., & Masa’deh, R. M. d. T., & Alkurdi, B. (2012). The effect of customer satisfaction upon customer retention in the Jordanian mobile market: An empirical investigation. European Journal of Economics, Finance and Administrative Sciences, 47(47), 69–78.
Alyammahi, A., Alshurideh, M., Kurdi, B. Al, & Salloum, S. A. (2020). The impacts of communication ethics on workplace decision making and productivity. In: International Conference on Advanced Intelligent Systems and Informatics, 488–500.
Alzoubi, Ali. (2021a). The impact of process quality and quality control on organizational competitiveness at 5-star hotels in Dubai. International Journal of Technology, Innovation and Management (IJTIM), 1(1), 54–68. https://doi.org/10.54489/ijtim.v1i1.14
Alzoubi, Asem. (2021b). Renewable Green hydrogen energy impact on sustainability performance. International Journal of Computations, Information and Manufacturing (IJCIM), 1(1), 94–110. https://doi.org/10.54489/ijcim.v1i1.46
Alzoubi, H., Ahmed, G., Al-Gasaymeh, A., & Alkurdi, B. (2019). Empirical study on sustainable supply chain strategies and its impact on competitive priorities: the mediating role of supply chain collaboration. Management Science Letters, 10(3), 703–708.
Alzoubi, H., Alshurideh, M., Kurdi, B. A., & Inairat, M. (2020). Do perceived service value, quality, price fairness and service recovery shape customer satisfaction and delight? A practical study in the service telecommunication context. Uncertain Supply Chain Management, 8(3). https://doi.org/10.5267/j.uscm.2020.2.005
Alzoubi, H. M., & Aziz, R. (2021). Does emotional intelligence contribute to quality of strategic decisions? the mediating role of open innovation. Journal of Open Innovation: Technology, Market, and Complexity, 7(2), 130. https://doi.org/10.3390/joitmc7020130
Alzoubi, H. M., Vij, M., Vij, A., & Hanaysha, J. R. (2021). What leads guests to satisfaction and loyalty in UAE five-star hotels? AHP analysis to service quality dimensions. Enlightening Tourism, 11(1), 102–135. https://doi.org/10.33776/et.v11i1.5056
Alzoubi, H. M., & Yanamandra, R. (2020). Investigating the mediating role of information sharing strategy on agile supply chain. Uncertain Supply Chain Management, 8(2), 273–284. https://doi.org/10.5267/j.uscm.2019.12.004
Alzoubi, H., Alshurideh, M., Kurdi, B., Akour, I., & Aziz, R. (2022). Does BLE technology contribute towards improving marketing strategies, customers’ satisfaction and loyalty? The role of open innovation. International Journal of Data and Network Science, 6(2), 449–460.
Alzoubi, H., & Ahmed, G. (2019). Do TQM practices improve organisational success? A case study of electronics industry in the UAE. International Journal of Economics and Business Research, 17(4), 459–472. https://doi.org/10.1504/IJEBR.2019.099975
Aziz, N., & Aftab, S. (2021). Data mining framework for nutrition ranking: methodology: SPSS modeller. International Journal of Technology, Innovation and Management (IJTIM), 1(1), 85–95.
Caicedo, J. C., & Lazebnik, S. (2015). Active object localization with deep reinforcement learning. In: Proceedings of the IEEE International Conference on Computer Vision, 2488–2496.
Cruz, A. (2021). Convergence between blockchain and the internet of things. International Journal of Technology, Innovation and Management (IJTIM), 1(1), 35–56.
Diamant, R., Francescon, R., & Zorzi, M. (2017). Topology-efficient discovery: A topology discovery algorithm for underwater acoustic networks. IEEE Journal of Oceanic Engineering, 43(4), 1200–1214.
Ding, G., Tan, Z., Zhang, J., & Zhang, L. (2013). Fingerprinting localization based on affinity propagation clustering and artificial neural networks. IEEE Wireless Communications and Networking Conference (WCNC), 2013, 2317–2322.
Ejaz, W., Naeem, M., Shahid, A., Anpalagan, A., & Jo, M. (2017). Efficient energy management for the internet of things in smart cities. IEEE Communications Magazine, 55(1), 84–91.
Eli, T. (2021). Students perspectives on the use of innovative and interactive teaching methods at the university of nouakchott al aasriya, mauritania: english department as a case study. International Journal of Technology, Innovation and Management (IJTIM), 1(2), 90–104.
Farouk, M. (2021). The Universal Artificial Intelligence Efforts to Face Coronavirus COVID-19. International Journal of Computations, Information and Manufacturing (IJCIM), 1(1), 77–93. https://doi.org/10.54489/ijcim.v1i1.47
Ghazal, T., Alshurideh, M., & Alzoubi, H. (2021a). Blockchain-Enabled Internet of Things (IoT) Platforms for Pharmaceutical and Biomedical Research. In: The International Conference on Artificial Intelligence and Computer Vision, 589–600.
Ghazal, T. M., Hasan, M. K., Alshurideh, M. T., Alzoubi, H. M., Ahmad, M., Akbar, S. S., Al Kurdi, B., & Akour, I. A. (2021b). IoT for smart cities: machine learning approaches in smart Healthcare—a review. Future Internet, 13(8), 218. https://doi.org/10.3390/fi13080218
Ghazal, T. M., Hasan, M. K., Hassan, R., Islam, S., Abdullah, S., Afifi, M. A., & Kalra, D. (2020). Security vulnerabilities, attacks, threats and the proposed countermeasures for the Internet of things applications. Solid State Technology, 63(1s), 2513–2521.
Ghazvini, A., Abdullah, S. N. H. S., Hasan, M. K., Kasim, D. Z. A., & Bin. (2020). Crime spatiotemporal prediction with fused objective function in time delay neural network. IEEE Access, 8, 115167–115183.
Gu, Y., Chen, Y., Liu, J., & Jiang, X. (2015). Semi-supervised deep extreme learning machine for Wi-Fi based localization. Neurocomputing, 166, 282–293.
Guergov, S., & Radwan, N. (2021). Blockchain Convergence: analysis of issues affecting IoT, AI and blockchain. International Journal of Computations, Information and Manufacturing (IJCIM), 1(1), 1–17. https://doi.org/10.54489/ijcim.v1i1.48
Hamadneh, S., Pedersen, O., Alshurideh, M., Kurdi, B. A., & Alzoubi, H. M. (2021a). An investigation of the role of supply chain visibility into the scottish blood supply chain. Journal of Legal, Ethical and Regulatory Issues, 24(Special Issue 1).
Hamadneh, Samer, Pedersen, O., & Al Kurdi, B. (2021b). An investigation of the role of supply chain visibility into the scottish bood supply chain. Journal of Legal, Ethical and Regulatory Issues, 24(Special Issue 1), 1–12.
Hanaysha, J. R., Al-Shaikh, M. E., Joghee, S., & Alzoubi, H. (2021a). Impact of innovation capabilities on business sustainability in small and medium enterprises. FIIB Business Review, 1–12. https://doi.org/10.1177/23197145211042232
Hanaysha, J. R., Al Shaikh, M. E., & Alzoubi, H. M. (2021b). Importance of marketing mix elements in determining consumer purchase decision in the retail market. International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 12(6), 56–72.
Hasan, M. K., Ahmed, M. M., Hashim, A. H. A., Razzaque, A., Islam, S., & Pandey, B. (2020). A novel artificial intelligence based timing synchronization scheme for smart grid applications. Wireless Personal Communications, 114(2), 1067–1084.
Hasan, M. K., Ismail, A. F., Islam, S., Hashim, W., Ahmed, M. M., & Memon, I. (2019). A novel HGBBDSA-CTI approach for subcarrier allocation in heterogeneous network. Telecommunication Systems, 70(2), 245–262.
Islam, S., Hashim, A.-H.A., Habaebi, M. H., & Hasan, M. K. (2017). Design and implementation of a multihoming-based scheme to support mobility management in NEMO. Wireless Personal Communications, 95(2), 457–473.
Islam, S., Khalifa, O. O., Hashim, A.-H.A., Hasan, M. K., Razzaque, M. A., & Pandey, B. (2020). Design and evaluation of a multihoming-based mobility management scheme to support inter technology handoff in PNEMO. Wireless Personal Communications, 114(2), 1133–1153.
Joghee, S., Alzoubi, H. M., Alshurideh, M., & Al Kurdi, B. (2021). The role of business intelligence systems on green supply chain management: empirical analysis of FMCG in the UAE. In: The International Conference on Artificial Intelligence and Computer Vision, 539–552.
Joghee, S., Alzoubi, H. M., & Dubey, A. R. (2020). Decisions effectiveness of FDI investment biases at real estate industry: Empirical evidence from Dubai smart city projects. International Journal of Scientific and Technology Research, 9(3), 3499–3503.
Kajioka, S., Mori, T., Uchiya, T., Takumi, I., & Matsuo, H. (2014). Experiment of indoor position presumption based on RSSI of Bluetooth LE beacon. In: 2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE), 337–339.
Kashif, A. A., Bakhtawar, B., Akhtar, A., Akhtar, S., Aziz, N., & Javeid, M. S. (2021). Treatment response prediction in hepatitis C patients using machine learning techniques. International Journal of Technology, Innovation and Management (IJTIM), 1(2), 79–89. https://doi.org/10.54489/ijtim.v1i2.24
Khan, M. A. (2021). Challenges facing the application of iot in medicine and healthcare. International Journal of Computations, Information and Manufacturing (IJCIM), 1(1), 39–55. https://doi.org/10.54489/ijcim.v1i1.32
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444.
Lee, C., & Ahmed, G. (2021). Improving IoT privacy, data protection and security concerns. International Journal of Technology, Innovation and Management (IJTIM), 1(1), 18–33. https://doi.org/10.54489/ijtim.v1i1.12
Lee, K., Azmi, N., Hanaysha, J., Alzoubi, H., & Alshurideh, M. (2022a). The effect of digital supply chain on organizational performance: An empirical study in Malaysia manufacturing industry. Uncertain Supply Chain Management, 10(2), 495–510.
Lee, K., Romzi, P., Hanaysha, J., Alzoubi, H., & Alshurideh, M. (2022b). Investigating the impact of benefits and challenges of IOT adoption on supply chain performance and organizational performance: An empirical study in Malaysia. Uncertain Supply Chain Management, 10(2), 537–550.
Li, L., Lv, Y., & Wang, F.-Y. (2016). Traffic signal timing via deep reinforcement learning. IEEE/CAA Journal of Automatica Sinica, 3(3), 247–254.
Luo, J., & Gao, H. (2016). Deep belief networks for fingerprinting indoor localization using ultrawideband technology. International Journal of Distributed Sensor Networks, 12(1), 5840916.
Mao, H., Alizadeh, M., Menache, I., & Kandula, S. (2016). Resource management with deep reinforcement learning.In: Proceedings of the 15th ACM Workshop on Hot Topics in Networks, 50–56.
Mehmood, T. (2021). Does information technology competencies and fleet management practices lead to effective service delivery? empirical evidence from E-commerce industry. International Journal of Technology, Innovation and Management (IJTIM), 1(2), 14–41.
Mehmood, T., Alzoubi, H. M., Alshurideh, M., Al-Gasaymeh, A., & Ahmed, G. (2019). Schumpeterian entrepreneurship theory: evolution and relevance. Academy of Entrepreneurship Journal, 25(4), 1–10.
Memon, I., Shaikh, R. A., Hasan, M. K., Hassan, R., Haq, A. U., & Zainol, K. A. (2020). Protect mobile travelers information in sensitive region based on fuzzy logic in IoT Ttechnology. Security and Communication Networks, 2020.
Memos, V. A., Psannis, K. E., Ishibashi, Y., Kim, B.-G., & Gupta, B. B. (2018). An efficient algorithm for media-based surveillance system (EAMSuS) in IoT smart city framework. Future Generation Computer Systems, 83, 619–628.
Miller, D. (2021). The Best Practice of Teach Computer Science Students to Use Paper Prototyping. International Journal of Technology, Innovation and Management (IJTIM), 1(2), 42–63. https://doi.org/10.54489/ijtim.v1i2.17
Minoli, D., Sohraby, K., & Occhiogrosso, B. (2017). IoT considerations, requirements, and architectures for smart buildings—Energy optimization and next-generation building management systems. IEEE Internet of Things Journal, 4(1), 269–283.
Misbahuddin, S., Zubairi, J. A., Saggaf, A., Basuni, J., Sulaiman, A., Al-Sofi, A., & others. (2015). IoT based dynamic road traffic management for smart cities. In: 2015 12th International Conference on High-Capacity Optical Networks and Enabling/Emerging Technologies (HONET), 1–5.
Mondol, E. P. (2021). The impact of block chain and smart inventory system on supply chain performance at retail industry. International Journal of Computations, Information and Manufacturing (IJCIM), 1(1), 56–76. https://doi.org/10.54489/ijcim.v1i1.30
Nair, K., Kulkarni, J., Warde, M., Dave, Z., Rawalgaonkar, V., Gore, G., & Joshi, J. (2015). Optimizing power consumption in iot based wireless sensor networks using bluetooth low energy. International Conference on Green Computing and Internet of Things (ICGCIoT), 2015, 589–593.
Nemati, S., Ghassemi, M. M., & Clifford, G. D. (2016). Optimal medication dosing from suboptimal clinical examples: A deep reinforcement learning approach. In: 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2978–2981.
Nurelmadina, N., Hasan, M. K., Memon, I., Saeed, R. A., Zainol Ariffin, K. A., Ali, E. S., Mokhtar, R. A., Islam, S., Hossain, E., Hassan, M., et al. (2021). A systematic review on cognitive radio in low power wide area network for industrial IoT applications. Sustainability, 13(1), 338.
Obaid, A. J. (2021). Assessment of smart home assistants as an IoT. International Journal of Computations, Information and Manufacturing (IJCIM), 1(1), 18–36. https://doi.org/10.54489/ijcim.v1i1.34
Perera, C., Zaslavsky, A., Christen, P., & Georgakopoulos, D. (2014). Sensing as a service model for smart cities supported by internet of things. Transactions on Emerging Telecommunications Technologies, 25(1), 81–93.
Pöhls, H. C., Angelakis, V., Suppan, S., Fischer, K., Oikonomou, G., Tragos, E. Z., Rodriguez, R. D., & Mouroutis, T. (2014). RERUM: Building a reliable IoT upon privacy-and security-enabled smart objects. IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2014, 122–127.
Radwan, N., & Farouk, M. (2021). The growth of internet of things (IoT) in the management of healthcare issues and healthcare policy development. International Journal of Technology, Innovation and Management (IJTIM), 1(1), 69–84. https://doi.org/10.54489/ijtim.v1i1.8
Saha, H. N., Auddy, S., Chatterjee, A., Pal, S., Sarkar, S., Singh, R., Singh, A. K., Sharan, P., Banerjee, S., Sarkar, R., & others. (2017). IoT solutions for smart cities. 2017 8th Annual Industrial Automation and Electromechanical Engineering Conference (IEMECON), 74–80.
Sanchez, L., Muñoz, L., Galache, J. A., Sotres, P., Santana, J. R., Gutierrez, V., Ramdhany, R., Gluhak, A., Krco, S., Theodoridis, E., et al. (2014). SmartSantander: IoT experimentation over a smart city testbed. Computer Networks, 61, 217–238.
Shakeel, P. M., El Tobely, T. E., Al-Feel, H., Manogaran, G., & Baskar, S. (2019). Neural network based brain tumor detection using wireless infrared imaging sensor. IEEE Access, 7, 5577–5588.
Shamout, M., Ben-Abdallah, B., Alshurideh, M., Alzoubi, H., Al Kurdi, B., & Hamadneh, S. (2022). A conceptual model for the adoption of autonomous robots in supply chain and logistics industry. Uncertain Supply Chain Management, 10, 1–16.
Sundhari, R. P. M., & Jaikumar, K. (2020). IoT assisted hierarchical computation strategic making (HCSM) and dynamic stochastic optimization technique (DSOT) for energy optimization in wireless sensor networks for smart city monitoring. Computer Communications, 150, 226–234.
Sweiss, N., Obeidat, Z. M., Al-Dweeri, R. M., Ahmad, M. K., & A., M. Obeidat, A., & Alshurideh, M. (2021). The moderating role of perceived company effort in mitigating customer misconduct within online brand communities (OBC). Journal of Marketing Communications. https://doi.org/10.1080/13527266.2021.1931942
Talari, S., Shafie-Khah, M., Siano, P., Loia, V., Tommasetti, A., & Catalão, J. P. S. (2017). A review of smart cities based on the internet of things concept. Energies, 10(4), 421.
Verma, P., Kumar, A., Rathod, N., Jain, P., Mallikarjun, S., Subramanian, R., Amrutur, B., Kumar, M. S. M., & Sundaresan, R. (2015). Towards an IoT based water management system for a campus. In: 2015 IEEE First International Smart Cities Conference (ISC2), 1–6.
Vlacheas, P., Giaffreda, R., Stavroulaki, V., Kelaidonis, D., Foteinos, V., Poulios, G., Demestichas, P., Somov, A., Biswas, A. R., & Moessner, K. (2013). Enabling smart cities through a cognitive management framework for the internet of things. IEEE Communications Magazine, 51(6), 102–111.
Wang, J., Zhang, X., Gao, Q., Yue, H., & Wang, H. (2016). Device-free wireless localization and activity recognition: A deep learning approach. IEEE Transactions on Vehicular Technology, 66(7), 6258–6267.
Wang, X., Ma, J., Wang, S., & Bi, D. (2009). Distributed energy optimization for target tracking in wireless sensor networks. IEEE Transactions on Mobile Computing, 9(1), 73–86.
Wang, X., Gao, L., Mao, S., & Pandey, S. (2015). DeepFi: Deep learning for indoor fingerprinting using channel state information. IEEE Wireless Communications and Networking Conference (WCNC), 2015, 1666–1671.
Zanella, A., Bui, N., Castellani, A., Vangelista, L., & Zorzi, M. (2014). Internet of things for smart cities. IEEE Internet of Things Journal, 1(1), 22–32.
Zhang, X., Wang, J., Gao, Q., Ma, X., & Wang, H. (2016). Device-free wireless localization and activity recognition with deep learning. IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops), 2016, 1–5.
Zygiaris, S. (2013). Smart city reference model: Assisting planners to conceptualize the building of smart city innovation ecosystems. Journal of the Knowledge Economy, 4(2), 217–231.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Ghazal, T.M., Hasan, M.K., Alzoubi, H.M., Alshurideh, M., Ahmad, M., Akbar, S.S. (2023). Internet of Things Connected Wireless Sensor Networks for Smart Cities. In: Alshurideh, M., Al Kurdi , B.H., Masa’deh, R., Alzoubi , H.M., Salloum, S. (eds) The Effect of Information Technology on Business and Marketing Intelligence Systems. Studies in Computational Intelligence, vol 1056. Springer, Cham. https://doi.org/10.1007/978-3-031-12382-5_107
Download citation
DOI: https://doi.org/10.1007/978-3-031-12382-5_107
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-12381-8
Online ISBN: 978-3-031-12382-5
eBook Packages: EngineeringEngineering (R0)