#python
WiFi DensePose uses WiFi signals and AI to detect human poses in real-time without cameras, tracking up to 10 people at 30 FPS with sub-50ms speed. Its Rust version boosts performance 810x faster, adds fall detection, activity tracking, and a disaster module for finding survivors under rubble via vital signs and 3D location. Install easily with `pip install wifi-densepose` for privacy-safe monitoring in homes, fitness, healthcare, or emergencies—saving lives and enhancing security without visual privacy risks.
https://github.com/ruvnet/wifi-densepose
WiFi DensePose uses WiFi signals and AI to detect human poses in real-time without cameras, tracking up to 10 people at 30 FPS with sub-50ms speed. Its Rust version boosts performance 810x faster, adds fall detection, activity tracking, and a disaster module for finding survivors under rubble via vital signs and 3D location. Install easily with `pip install wifi-densepose` for privacy-safe monitoring in homes, fitness, healthcare, or emergencies—saving lives and enhancing security without visual privacy risks.
https://github.com/ruvnet/wifi-densepose
GitHub
GitHub - ruvnet/wifi-densepose: Production-ready implementation of InvisPose - a revolutionary WiFi-based dense human pose estimation…
Production-ready implementation of InvisPose - a revolutionary WiFi-based dense human pose estimation system that enables real-time full-body tracking through walls using commodity mesh routers - ...