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Federated Learning in Smart City Sensing: Challenges and Opportunities
Ji Chu Jiang1, Burak Kantarci1, Sema Oktug2
1School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON K1N 6N5, Canada.
Sensors (Basel, Switzerland)
|November 4, 2020
Summary
Federated Learning addresses security and privacy concerns in smart city sensing by enabling decentralized AI model training. This approach enhances data participation for improved smart city services.
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2026-06-19T13:38:47.766632+00:00
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