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Applications of federated learning in smart cities: recent advances, taxonomy, and open challenges - 2021

Applications Of Federated Learning In Smart Cities: Recent Advances, Taxonomy, And Open Challenges

Research Area:  Machine Learning

Abstract:

Federated learning (FL) plays an important role in the development of smart cities. With the evolution of big data and artificial intelligence, issues related to data privacy and protection have emerged, which can be solved by FL. In this paper, the current developments in FL and its applications in various fields are reviewed. With a comprehensive investigation, the latest research on the application of FL is discussed for various fields in smart cities. We explain the current developments in FL in fields, such as the Internet of Things (IoT), transportation, communications, finance, and medicine. First, we introduce the background, definition, and key technologies of FL. Then, we review key applications and the latest results. Finally, we discuss the future applications and research directions of FL in smart cities.

Keywords:  

Author(s) Name:  Zhaohua Zheng, Yize Zhou, Yilong Sun, Zhang Wang, Boyi Liu, Keqiu Li

Journal name:  Connection Science

Conferrence name:  

Publisher name:  Taylor & Francis

DOI:  https://doi.org/10.1080/09540091.2021.1936455

Volume Information: