Project-19-Fallower: Real-Time UWB Based Human Fall Detection and Tracking System

Directed the R&D and AI strategy for Fallower, a non-intrusive safety monitoring system utilizing Ultra-Wideband (UWB) radar technology. Engineered a privacy-preserving alternative to camera-based or wearable solutions, employing machine learning algorithms to classify human movement patterns and detect fall anomalies with high precision, triggering instant alerts to caregivers. Supported by the TUBITAK 1501 program. (2024-Present)