11st of 52 in Open models
ruview
WiFi CSI sensing on ESP32 for presence, breathing, heart rate and pose
- Stars
- 101.9k
- License
- MIT
- Last commit
- Oct 2026
- Last release
- Oct 2026
- Language
- Rust
44,706 on 10 Apr 2026101,939 on 30 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
RuView reads Channel State Information from ESP32-S3/C6 nodes and derives presence, person count, breathing (6–30 BPM), heart rate (40–120 BPM), falls and 17-keypoint pose without cameras. It is written in Rust, with pretrained models on Hugging Face, Home Assistant, Matter and HomeKit integration, and an npm MCP toolkit for AI-guided setup. Several accuracy figures are self-reported, and the README says the on-device pose model is a first cut.
Who it is for: Self-hosters and researchers needing camera-free presence and vitals sensing
Strengths
- Runs on roughly $9 ESP32 nodes; the pretrained encoder fits in 8 KB at 4-bit
- Publishes 21 Home Assistant MQTT entities per node, plus Matter and Apple Home bridges
- Pretrained weights on Hugging Face, plus a phase-variance presence fallback needing no model
- README retracts an earlier accuracy claim and flags unvalidated vitals and synthetic RF accuracy
Weaknesses
- Live sensing needs ESP32-S3/C6 CSI firmware; the Docker image runs simulated data
- Committed on-device pose model scores PCK@20 of 3.0% and its runtime path is a stub
- Through-wall range is about 5 m and signal-dependent
- Very large README and feature surface; hard to tell which parts are production-ready
What it needs
- GPU optional
- Docker + Compose
- Needs ESP32-S3 or ESP32-C6 boards, Cognitum Seed (optional), Home Assistant / MQTT (optional)
- Models: safetensors, RVF, Candle
- port 3000
Quick answers
Is ruview open source?
Yes. Its code is on GitHub under the MIT license.
Can you run ruview with Docker?
Yes. Its repository has a Docker setup: a Dockerfile, a Compose file or a published image.
Does ruview need a GPU?
No. It runs on a CPU and can use a GPU when you have one.
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