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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.

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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