AI-Assisted Predictive Analytics for Smart City IoT Applications

Authors

  • Ankur Singh * School of Computer Science Engineering, KIIT University, Bhubaneswar, India.
  • Esraa Aljubarah Independent Researcher, Nabels, Palestine.

https://doi.org/10.48313/siot.v3i1.115

Abstract

As urbanization accelerates globally, cities face increasing challenges related to infrastructure, transportation, and resource management. The integration of Internet of Things (IoT) devices within smart city frameworks offers significant opportunities to optimize urban operations through data-driven decision-making. This paper explores the role of AI-assisted predictive analytics in enhancing IoT applications for smart cities. By analyzing various case studies, methodologies, and frameworks, we elucidate how predictive analytics can transform urban management, improve quality of life, and foster sustainable development.

 

Keywords:

Artificial intelligence, Predictive analytics, Smart cities, Internet of things

References

  1. [1] Giffinger, R., Fertner, C., Kramar, H., & Meijers, E. (2007). City-ranking of European medium-sized cities. 51st IFHP World Congress–Futures of Cities, 9(1), International Federation for Housing and Planning (IFHP) 1–12. https://www.researchgate.net/publication/313716484
  2. [2] Chourabi, H., Nam, T., Walker, S., Gil Garcia, J. R., Mellouli, S., Nahon, K., & Scholl, H. J. (2012). Understanding smart cities: An integrative framework. 2012 45th Hawaii International Conference on System Sciences (pp. 2289–2297). IEEE. https://doi.org/10.1109/HICSS.2012.615
  3. [3] Albino, V., Berardi, U., & Dangelico, R. M. (2015). Smart cities: Definitions, dimensions, performance, and initiatives. Journal of Urban Technology, 22(1), 3–21. https://doi.org/10.1080/10630732.2014.942092
  4. [4] Batty, M., Axhausen, K. W., Giannotti, F., Pozdnoukhov, A., Bazzani, A., Wachowicz, M., & Portugali, Y. (2012). Smart cities of the future. The European Physical Journal Special Topics, 214(1), 481–518. https://doi.org/10.1140/epjst/e2012-01703-3%0A%0A
  5. [5] Kitchin, R. (2014). The data revolution: Big data, open data, data infrastructures and their consequences. Sage. https://doi.org/10.4135/9781473909472%0A
  6. [6] Rababah, B., Alam, T., & Eskicioglu, R. (2020). The next generation internet of things architecture towards distributed intelligence: Reviews, applications, and research challenges. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 12(2), 11–19. https://jtec.utem.edu.my/jtec/article/view/5535
  7. [7] Barlow, G. J., Smith, S. F., Xie, X.-F., & Rubinstein, Z. B. (2014). Real-time traffic control for urban environments: Expanding the Surtrac testbed network. Proceedings of the World Congress on Intelligent Transportation Systems and ITS America Annual Meeting, 3240–3249. https://publications.ri.cmu.edu/real-time-traffic-control-for-urban-environments-expanding-the-surtrac-testbed-network
  8. [8] IEEE Smart Cities. (2023). Data analytics for smart cities: Part 2. https://resourcecenter.smartcities.ieee.org/publications/enewsletters/smcnl0042
  9. [9] European Commission. (2016). Analysing the potential for wide scale roll-out of integrated smart cities and communities solutions: Final report. https://energy.ec.europa.eu/publications/analysing-potential-wide-scale-roll-out-integrated-smart-cities-and-communities-solutions_en
  10. [10] Barcelona City Council. (2023). Smart city. https://ajuntament.barcelona.cat/digital/en/digital-transformation/smart-city

Downloads

Published

2026-03-01

Issue

Vol. 3 No. 1 (2026): Smart Internet of Things

Section

Articles

How to Cite

Singh, A., & Aljubarah, E. . (2026). AI-Assisted Predictive Analytics for Smart City IoT Applications. Smart Internet of Things, 3(1), 1-8. https://doi.org/10.48313/siot.v3i1.115