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

doi:10.1080/09540091.2021.1936455

UM > THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)

Residential College	false
Status	即將出版Forthcoming
	Applications of federated learning in smart cities: recent advances, taxonomy, and open challenges
	Zheng, Zhaohua 1,2; Zhou, Yize 3; Sun, Yilong 4; Wang, Zhang 5; Liu, Boyi 6; Li, Keqiu 7
	2022-06
Source Publication	CONNECTION SCIENCE
ISSN	0954-0091
Volume	34 Issue:1 Pages:1-28
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.
Keyword	Federated Learning Smart City Internet Of Things
DOI	10.1080/09540091.2021.1936455
URL	View the original
Indexed By	SCIE
Language	英語English
WOS Research Area	Computer Science
WOS Subject	Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS ID	WOS:000657955800001
Scopus ID	2-s2.0-85107461361
Fulltext Access	View Full-Text via DOI View Full-Text via Web of Science View Full-Text via Scopus
Citation statistics
Document Type	Journal article
Collection	THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
Corresponding Author	Zheng, Zhaohua
Affiliation	1.School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University,Tianjin, People’s Republic of China 2.School of CyberSpace Security (School of Cryptology), Hainan University,Haikou, People’s Republic of China 3.School of Science, Hainan University, Haikou, People’s Republic of China 4.School of Management, Hainan University, Haikou, People’s Republic of China 5.School of Information andCommunication Engineering, Hainan University, Haikou, People’s Republic of China 6.State Key Laboratory ofInternet of Things for Smart City (IoTSC), University of Macau, Taipa, People’s Republic of China 7.College ofIntelligence and Computing, Tianjin University, Tianjin, People’s Republic of China
Recommended Citation GB/T 7714	Zheng, Zhaohua,Zhou, Yize,Sun, Yilong,et al. Applications of federated learning in smart cities: recent advances, taxonomy, and open challenges[J]. CONNECTION SCIENCE, 2022, 34(1), 1-28.
APA	Zheng, Zhaohua., Zhou, Yize., Sun, Yilong., Wang, Zhang., Liu, Boyi., & Li, Keqiu (2022). Applications of federated learning in smart cities: recent advances, taxonomy, and open challenges. CONNECTION SCIENCE, 34(1), 1-28.
MLA	Zheng, Zhaohua,et al."Applications of federated learning in smart cities: recent advances, taxonomy, and open challenges".CONNECTION SCIENCE 34.1(2022):1-28.

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