AI IoT-Powered Smart City Energy Management Systems: A Framework for Efficient Resource Management
DOI:
https://doi.org/10.48313/siot.v2i1.297Keywords:
Smart city, Artificial intelligence, Internet of things, Resource management, Scalability, Urban infrastructureAbstract
This document presents a scalable IoT framework powered by Artificial Intelligence (AI) aimed at enhancing resource management within smart city infrastructures, focusing specifically on water, energy, waste, and transportation. With the increase in urban populations, the need for efficient resource allocation and waste management escalates, necessitating systems capable of processing and responding to data in real time. The suggested framework features a multilayered IoT system architecture, attributes for scalability, sophisticated data processing algorithms, and security protocols to manage extensive IoT device installations and data streams within urban environments. When evaluated against current systems, the framework shows significant improvements in resource optimization and overall efficiency. Performance indicators, comparative studies, and security assessments highlight the framework's strength and dependability, setting the stage for sustainable development in smart cities.
References
Mohanty, S. P., Choppali, U., & Kougianos, E. (2016). Everything you wanted to know about smart cities: The internet of things is the backbone. IEEE consumer electronics magazine, 5(3), 60–70. https://doi.org/10.1109/MCE.2016.2556879
Babar, M., & Sohail Khan, M. (2021). ScalEdge: A framework for scalable edge computing in Internet of things-based smart systems. International journal of distributed sensor networks, 17(7), 15501477211035332. https://doi.org/10.1177/15501477211035332
Khatoun, R., & Zeadally, S. (2016). Smart cities: concepts, architectures, research opportunities. Communications of the acm, 59(8), 46–57. https://doi.org/10.1145/2858789
Cardone, G., Foschini, L., Bellavista, P., Corradi, A., Borcea, C., Talasila, M., & Curtmola, R. (2013). Fostering participaction in smart cities: a geo-social crowdsensing platform. IEEE communications magazine, 51(6), 112–119. https://doi.org/10.1109/MCOM.2013.6525603
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. https://doi.org/10.1109/JIOT.2014.2306328
Sheng, Z., Yang, S., Yu, Y., Vasilakos, A. V, McCann, J. A., & Leung, K. K. (2013). A survey on the ietf protocol suite for the internet of things: Standards, challenges, and opportunities. IEEE wireless communications, 20(6), 91–98. https://doi.org/10.1109/MWC.2013.6704479
Sheth, A., Henson, C., & Sahoo, S. S. (2008). Semantic sensor web. IEEE internet computing, 12(4), 78–83. https://doi.org/10.1109/MIC.2008.87
Mocanu, E., Nguyen, P. H., Gibescu, M., & Kling, W. L. (2016). Deep learning for estimating building energy consumption. Sustainable energy, grids and networks, 6, 91–99. https://doi.org/10.1016/j.segan.2016.02.005
Bengio, Y., & others. (2009). Learning deep architectures for AI. Foundations and trends in machine learning, 2(1), 1–127. http://dx.doi.org/10.1561/2200000006
Cartella, F., Lemeire, J., Dimiccoli, L., & Sahli, H. (2015). Hidden Semi-Markov models for predictive maintenance. Mathematical problems in engineering, 2015(1), 278120. https://doi.org/10.1155/2015/278120
Hou, X., Li, Y., Chen, M., Wu, D., Jin, D., & Chen, S. (2016). Vehicular fog computing: A viewpoint of vehicles as the infrastructures. IEEE transactions on vehicular technology, 65(6), 3860–3873. https://doi.org/10.1109/TVT.2016.2532863
Mohapatra, H., Mishra, S. R., Rath, A. K., & Kolhar, M. (2025). Sustainable cities and communities: Role of network sensing system in action. Networked sensing systems, 173–198. https://doi.org/10.1002/9781394310890.ch7
Council, B. C. (2021). Barcelona smart city: Technology and services to manage the city efficiently. http://ndc.hust.edu.cn/barcelona_smart_city.pdf
(IDA), I. D. A. of S. (2018). Smart nation Singapore: A plan for the future. https://www.smartnation.gov.sg/
Solanas, A., Patsakis, C., Conti, M., Vlachos, I. S., Ramos, V., Falcone, F. (2014). Smart health: A context-aware health paradigm within smart cities. IEEE communications magazine, 52(8), 74–81. https://doi.org/10.1109/MCOM.2014.6871673
Yigitcanlar, T. (2015). Smart cities: An effective urban development and management model? Australian planner, 52(1), 27–34. https://doi.org/10.1080/07293682.2015.1019752
Al-Turjman, F., & Abujubbeh, M. (2019). IoT-enabled smart grid via SM: An overview. Future generation computer systems, 96, 579–590. https://doi.org/10.1016/j.future.2019.02.012
Mohapatra, H. (2021). Socio-technical challenges in the implementation of smart city. International conference on innovation and intelligence for informatics, computing, and technologies (3ict) (pp. 57–62). (3ICT). https://ieeexplore.ieee.org/abstract/document/9581905
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