ruvnet/RuView

What it solves

RuView transforms ordinary WiFi signals into a spatial intelligence system. It allows for the detection of people, tracking of movement, and monitoring of vital signs (breathing and heart rate) through walls and in the dark, eliminating the need for cameras or wearable devices.

How it works

The system uses Channel State Information (CSI) from low-cost ESP32 sensors to capture disturbances in radio waves caused by human presence and activity. These signals are processed using pretrained models (available on Hugging Face) and spiking neural networks that adapt to local environments. The platform can run entirely on edge hardware, such as an ESP32 mesh paired with a Cognitum Seed, and integrates with smart-home ecosystems like Home Assistant, Apple Home, Google Home, and Amazon Alexa.

Who it’s for

It is designed for smart-home developers, researchers, and users interested in privacy-preserving environmental monitoring, health tracking (e.g., sleep quality and apnea screening), and security (e.g., fall detection and occupancy sensing).

Highlights

• Contactless Vitals: Real-time monitoring of breathing (6–30 BPM) and heart rate (40–120 BPM).
• Camera-Free Pose Estimation: Estimates 17 body keypoints using WiFi CSI signals.
• Privacy-First Edge AI: Runs locally on ESP32 hardware without requiring cloud connectivity or internet.
• Broad Integration: Native support for Matter, Home Assistant, and major voice assistants.
• Extensive Module Catalog: Includes over 100 "Cogs" (edge modules) for specific use cases like queue length, customer flow, and elderly inactivity anomalies.