Demo: FedCampus: A Real-world Privacy-preserving Mobile Application for Smart Campus via Federated Learning & Analytics
In this demo, we introduce FedCampus, a privacy-preserving mobile application for smart \underline{campus} with \underline{fed}erated learning (FL) and federated analytics (FA). FedCampus enables cross-platform on-device FL/FA for both iOS and Android, supporting continuously models and algorithms d...
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Zusammenfassung: | In this demo, we introduce FedCampus, a privacy-preserving mobile application
for smart \underline{campus} with \underline{fed}erated learning (FL) and
federated analytics (FA). FedCampus enables cross-platform on-device FL/FA for
both iOS and Android, supporting continuously models and algorithms deployment
(MLOps). Our app integrates privacy-preserving processed data via differential
privacy (DP) from smartwatches, where the processed parameters are used for
FL/FA through the FedCampus backend platform. We distributed 100 smartwatches
to volunteers at Duke Kunshan University and have successfully completed a
series of smart campus tasks featuring capabilities such as sleep tracking,
physical activity monitoring, personalized recommendations, and heavy hitters.
Our project is opensourced at https://github.com/FedCampus/FedCampus_Flutter.
See the FedCampus video at https://youtu.be/k5iu46IjA38. |
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DOI: | 10.48550/arxiv.2409.00327 |