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Federated learning for smart cities: A comprehensive survey - ScienceDirect
Source: sciencedirect.com
Article summary:
1. This paper provides an overview of the current and future developments of Federated Learning (FL) for smart cities.
2. It discusses the concept of FL for smart cities, and numerous FL integrated smart city applications, including smart transportation systems, smart healthcare, smart grid, and more.
3. It outlines and analyzes various research challenges and prospects for the development of FL for smart cities.
Article analysis:
The article is generally reliable in its presentation of the topic at hand. The authors provide a comprehensive overview of the current and future developments of Federated Learning (FL) for smart cities, discussing the concept of FL for smart cities as well as numerous FL integrated applications such as transportation systems, healthcare, grid, etc. The authors also outline various research challenges and prospects for the development of FL for smart cities.
The article does not appear to be biased or one-sided in its reporting; it presents both sides equally by providing an overview of both current developments as well as potential future advancements in this field. Furthermore, it does not appear to contain any promotional content or partiality towards any particular viewpoint or opinion on this topic.
The article does not appear to contain any unsupported claims or missing points of consideration; all claims are supported by evidence from relevant sources such as reports from the United Nations and World Bank. Additionally, all counterarguments are explored thoroughly throughout the article.
The only potential issue with this article is that it does not explicitly note any possible risks associated with using Federated Learning (FL) in Smart Cities applications; however, this is likely due to space constraints rather than intentional omission on behalf of the authors.