# ruvnet/RuView

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

Repository: https://github.com/ruvnet/RuView
Canonical: https://ross.abutalabs.com/products/ruview
Homepage: https://Cognitum.One/RuView
Language: Rust
License: MIT
License Family: permissive
Topics: densepose, wifi, esp32, monitoring, rf, wifi-security, self-learning, firmware, pose-estimation, spatial-intelligence, home-assistant, home-automation, skills, networking, claude, iot, react, typescript, npm, awesome
Last push: 2026-08-26T18:40:57+00:00

## Health v2 (maintenance only)
Score: 81/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 99, release rhythm 87, longevity 32
- inputs: {"age_days": 452, "days_push": 7, "days_rel": 8, "gap_med": 0, "n_releases_24m": 284}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 91756, forks 12178 (observed 2026-08-28T04:12:23.362987+00:00)

## What it is
RuView is a WiFi sensing platform that uses Channel State Information (CSI) from commodity WiFi hardware like ESP32 to detect presence, track movement, and monitor vital signs without cameras. It integrates with smart home ecosystems including Home Assistant, Apple Home, Google Home, and Alexa via MQTT and Matter.

## Use cases
- detect human presence through walls without cameras
- monitor breathing and heart rate via WiFi signals
- track room occupancy for home automation
- detect falls or distress in elderly care
- build a privacy-preserving security and monitoring system
- integrate presence and vitals into Home Assistant or Matter

## When to choose
- you need camera-free, privacy-preserving presence and vital-sign monitoring
- you want to sense occupancy through walls or in darkness
- you already run Home Assistant or a Matter-compatible smart home
- you have low-cost ESP32 or CSI-capable WiFi hardware

## When to avoid
- you need precise visual identification or video evidence
- your WiFi hardware does not expose CSI data
- you need a plug-and-play consumer product rather than a self-hosted platform
- you require medically certified vital-sign measurements

## Facets
- artifact type: application
- maturity: active
- function: monitoring, machine-learning, iot, analytics, sdk
- domain: iot, computer-vision, artificial-intelligence, self-hosted
- platform: iot, self-hosted, cross-platform
- tags: wifi-sensing, csi, densepose, presence-detection, vital-signs, home-assistant, matter, mqtt, privacy-preserving, rust, linux, docker

## Member repositories
- ruvnet/RuView (main) score 81

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:23.362987+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:13:50.728219+00:00, confidence not recorded.
  - readme: https://github.com/ruvnet/RuView (fetched 2026-08-28T04:12:23.362987+00:00, sha 0c65e7e143bb)
  - homepage: https://Cognitum.One/RuView (fetched 2026-08-28T17:35:55.356074+00:00, sha 355626515ef0)
  - registry_pypi: https://pypi.org/pypi/ruview/json (fetched 2026-08-28T17:35:55.364560+00:00, sha 73cba5fae42f)
- Data as of 2026-08-30T08:39:29.467469+00:00.