Abinand2631/Wifi-Vision

Teach three $10 ESP32-S3 boards to recognise what you're doing from WiFi alone, with your webcam as the teacher

Human pose estimation using WiFi Channel State Information (CSI) and deep learning — enabling camera-free sensing through walls.

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

WiFi CSI human sensing for Python presence, fall detection, breathing rate, activity classification, and occupancy counting from an ESP32. No camera, no cloud, no PyTorch/CUDA at runtime.

Applications based on Wi-Fi CSI (Channel state information), such as indoor positioning, human detection

Wi-Fi motion sensing platform for ESP32. C++ SDK, ESPHome, Native, and Matter frontends, browser tools, and a CLI for the full device lifecycle. GPLv3 and commercial licensing.

π RuView turns commodity WiFi signals into real-time spatial intelligence, vital sign monitoring, and presence detection — all without a single pixel of video.

Learning algorithm for human activity recognition with a commercial IEEE 802.11ac router

Detect motion, presence and breathing through walls with ordinary WiFi. ESP32-S3 captures 802.11 CSI, a Raspberry Pi 4 runs the DSP, a browser dashboard shows it live.