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

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:

• Federated learning
• smart city
• internet of things

Acknowledgments

The authors would like to thank the anonymous reviewers for their constructive and insightful comments on this paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work is supported by the Natural Science Foundation of Hainan Province (Grant No. 619QN194) and the Key Project of Students' Innovation and Entrepreneurship of Hainan University (Grant No. 20210114).