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Smart city article details

Title	Empowering Smart Cities Through Federated Learning An Overview
ID_Doc	22922
Authors	Jarour A.
Year	2024
Published	2024 28th International Conference on System Theory, Control and Computing, ICSTCC 2024 - Proceedings
DOI	http://dx.doi.org/10.1109/ICSTCC62912.2024.10744688
Abstract	This paper provides the role of Federated Learning (FL) in empowering smart cities, with an emphasis on technology, applications, future directions, approaches and strategies, and the FL environment as a part of this overview, through investigating and discussing the latest research on applying FL in a variety of fields in smart cities by using the literature review as a methodology in the paper. FL is a decentralized machine learning technique that addresses data collecting, privacy, and security issues. Additionally, FL offers potential solutions for problems in smart cities, including enhancing data privacy, real-time anomaly detection, resource optimization, environmental monitoring, and smart grid management. Moreover, the paper presents some applications and relevant work in the FL in smart cities fields and summarizes them to introduce the main limitations of their work and future directions. © 2024 IEEE.
Author Keywords	Federated Learning; Internet of Things; Privacy and Security; Smart Cities

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