An AI–IoT integrated smart grid model for resilient and sustainable urban energy management

Authors

  • Mingyue Wang * School of computer and information, Lanzhou University of Technology, China. https://orcid.org/0009-0005-5983-8646
  • Aleksandar Dimov Faculty of Mathematics and Informatics (FMI), Sofia University, Bulgaria.

https://doi.org/10.22105/sci.v2i3.46

Abstract

As urban populations grow, cities face increasing pressure to manage energy consumption efficiently. The advent of IoT-based smart grid technologies provides a promising solution, enabling real-time monitoring, data analysis, and predictive maintenance to optimize energy use. This paper investigates various IoT applications in smart grids, focusing on their role in urban energy management. It examines Advanced Metering Infrastructure (AMI), Demand Response (DR), and Distributed Energy Resource (DER) integration. Through a comparative analysis of current strategies, the study highlights the strengths and challenges of IoT-based smart grids in urban areas and proposes future improvements for scalability and security. This research aims to advance smart grid capabilities to meet the dynamic energy demands of urban environments.

Keywords:

Internet of things, Smart grid, Urban energy management, Demand response, Advanced metering infrastructure

References

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Published

2025-09-26

Issue

Vol. 2 No. 3 (2025): Smart City Insights

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Articles

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How to Cite

Wang, M., & Dimov, A. (2025). An AI–IoT integrated smart grid model for resilient and sustainable urban energy management. Smart City Insights, 2(3), 169-176. https://doi.org/10.22105/sci.v2i3.46

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