AI-powered resource allocation in smart city IoT networks
Abstract
As urbanization accelerates, smart city frameworks incorporating Internet of Things (IoT) networks have become essential for efficient city management. AI-powered resource allocation plays a critical role by enabling adaptive, data-driven optimization of these networks, ensuring effective utilization of computational resources, bandwidth, and energy. This report provides an overview of AI methodologies applied to resource allocation, examines technical and operational challenges, and explores future advancements.
Keywords:
Urbanization, Smart city, Internet of things, AI-powered resource allocation, Data-driven optimizationReferences
- [1] Mishra, P., & Singh, G. (2023). Energy management systems in sustainable smart cities based on the internet of energy: A technical review. Energies, 16(19), 6903. https://doi.org/10.3390/en16196903
- [2] Van Hoang, T. (2024). Impact of integrated artificial intelligence and internet of things technologies on smart city transformation. Journal of technical education science, 19(Special Issue 01), 64–73. https://doi.org/10.54644/jte.2024.1532
- [3] Bellini, P., Nesi, P., & Pantaleo, G. (2022). IoT-enabled smart cities: A review of concepts, frameworks and key technologies. Applied sciences, 12(3), 1607. https://doi.org/10.3390/app12031607
- [4] Swain, B., Raj, P., Singh, K., Singh, Y., Singh, S., & Mohapatra, H. (2025). Ethical implications and mitigation strategies for public safety and security in smart cities for securing tomorrow. Convergence of cybersecurity and cloud computing (pp. 419–436). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-6859-6.ch019
- [5] Mohapatra, H. (2025). The role of 6G in empowering smart cities enabling ubiquitous connectivity and intelligent infrastructure. In RFID, microwave circuit, and wireless power transfer enabling 5/6g communication (pp. 231–254). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-8799-3.ch008
- [6] Mhlanga, D., & Shao, D. (2025). AI-optimized urban resource management for sustainable smart cities. In Financial inclusion and sustainable development in sub-saharan Africa (pp. 96–116). Routledge. https://B2n.ir/r67035
- [7] Wolniak, R., & Stecuła, K. (2024). Artificial intelligence in smart cities—applications, barriers, and future directions: A review. Smart cities, 7(3), 1346–1389. https://doi.org/10.3390/smartcities7030057
- [8] Firoozi, A. A., & Firoozi, A. A. (2025). Impact of integrating artificial intelligence and the internet of things in urban system management. Deep Science Publishing. https://doi.org/10.70593/978-93-49307-08-7_7
- [9] Ponnusamy, S., Chourasia, H., Rathod, S. B., & Patil, D. (2004). Ai-driven traffic management systems: Reducing congestion and improving safety in smart cities. In Smart cities (pp. 96–121). CRC Press. https://doi.org/10.1201/9781003442660
- [10] Almatar, K. M. (2024). Implementing AI-driven traffic signal systems for enhanced traffic management in dammam. International journal of sustainable development & planning, 19(2). https://doi.org/10.18280/ijsdp.190236