Applications of Federated Learning in Smart Cities: Recent Advances, Taxonomy, and Open Challenges
This survey provides a comprehensive overview of federated learning applications and challenges for researchers and practitioners in smart city development.
This paper reviews the current developments and applications of federated learning in smart cities, addressing data privacy concerns arising from big data and AI. It summarizes recent research across various domains like IoT, transportation, and healthcare.
Federated learning plays an important role in the process of smart cities. With the development of big data and artificial intelligence, there is a problem of data privacy protection in this process. Federated learning is capable of solving this problem. This paper starts with the current developments of federated learning and its applications in various fields. We conduct a comprehensive investigation. This paper summarize the latest research on the application of federated learning in various fields of smart cities. In-depth understanding of the current development of federated learning from the Internet of Things, transportation, communications, finance, medical and other fields. Before that, we introduce the background, definition and key technologies of federated learning. Further more, we review the key technologies and the latest results. Finally, we discuss the future applications and research directions of federated learning in smart cities.