🚨 Someone just turned your WiFi router into a full-body surveillance system. No cameras. No wearables. No video. Just radio waves. It's called RuView. It uses the WiFi signals already in your room to detect human poses, track breathing, measure heart rate, and see through walls. Not a concept. Not a research paper. Working code you can run right now. Here's what this thing actually does: → Tracks full 17-point body pose using only WiFi signals → Detects breathing rate (6-30 BPM) without touching anyone → Measures heart rate (40-120 BPM) from across the room → Sees through walls, furniture, and debris up to 5 meters deep → Tracks multiple people simultaneously with zero identity swaps → Self-learns from raw WiFi data. No labeled datasets needed Here's how it works: WiFi signals pass through your room and hit the human body. The body scatters those signals differently based on position, breathing, even heartbeat. RuView reads that scattering pattern and reconstructs everything. A mesh of 4 ESP32 nodes ($48 total) gives you 360-degree coverage with 12 measurement links, 20 Hz updates, and sub-30mm precision. Here's the wildest part: It has a disaster response mode called WiFi-Mat. It detects survivors trapped under rubble through concrete walls, classifies injury severity using START triage protocol, and estimates 3D position. The kind of tool that saves lives after earthquakes. The Rust implementation processes 54,000 frames per second. That's 810x faster than the Python version. The entire Docker image is 132 MB. The AI model fits in 55 KB of memory. Runs on an $8 ESP32 chip. Train once, deploy in any room. No retraining. No recalibration. 1,100+ tests. SHA-256 verified capability audit. 22.4K GitHub stars. 2.7K forks. MIT License. 100% Open Source.