FedWiLoc: Federated Learning for Private WiFi Indoor Positioning

This research explores a practical application of federated learning for privacy-preserving indoor localization, addressing a key challenge in WiFi-based positioning. The paper's contribution lies in enabling location services without compromising user data privacy, which is crucial for widespread adoption.