ruvnet/RuView

**ruvnet/RuView**

π RuView: WiFi DensePose turns commodity WiFi signals into real-time human pose estimation, vital sign monitoring, and presence detection — all without a single pixel of video.π RuView See through walls with WiFi. WiFi DensePose turns commodity WiFi signals into real-time human pose estimation, vital sign monitoring, and presence detection — all without a single pixel of video. By analyzing Channel State Information (CSI) disturbances caused by human movement, the system reconstructs body position, breathing rate, and heartbeat using physics-based signal processing and machine learning. Edge modules are small programs that run directly on the ESP32 sensor — no internet needed, no cloud fees, instant response. What How Speed Pose estimation CSI subcarrier amplitude/phase → DensePose UV maps 54K fps (Rust) Breathing detection Bandpass 0.1-0.5 Hz → FFT peak 6-30 BPM Heart rate Bandpass 0.8-2.0 Hz → FFT peak 40-120 BPM Presence sensing RSSI variance + motion band power < 1ms latency Through-wall Fresnel zone geometry + multipath modeling Up to 5m depth # 30 seconds to live sensing — no toolchain required docker pull ruvnet/wifi-densepose:latest docker run -p 3000:3000 ruvnet/wifi-densepose:latest # Open http://localhost:3000 [!NOTE] CSI-capable hardware required...

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