Rankings/RuView

RuView

ruvnet/RuView

Turns ordinary WiFi into radar to monitor breathing, movement, and presence without cameras, a privacy-protecting home sensing solution.

π RuView: WiFi DensePose turns commodity WiFi signals into real-time human pose estimation, vital sign monitoring, and presence detection — all without a single pixel of video.

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Turns ordinary WiFi into radar to monitor breathing, movement, and presence without cameras, a privacy-protecting home sensing solution.

📂 Security & Privacy🤖 AI Related💻 Rust📄 MIT

AI Summary

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What This Project Does

Simply put, it turns existing home WiFi signals into a "seeing eye." Without installing cameras, it perceives if there are people in the room, what they are doing, and even measures breathing and heart rate via radio wave changes.

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What Problems It Solves

Solves the conflict of "wanting to monitor family safety without invading privacy." Traditional solutions require cameras, creating a sense of being watched, and cannot penetrate walls. It replaces cameras to achieve fall detection, sleep monitoring, and intrusion prevention while protecting privacy.

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Who It's For

1. Home users concerned about the safety of elderly people living alone or children.

2. People extremely sensitive to privacy who refuse camera installation at home.

3. Geeks and developers who like tinkering with hardware and WiFi principles.

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Typical Use Cases

  • Bedroom Sleep Monitoring: Place it by the bed while sleeping to record breathing quality without wearable devices.
  • Living Room Safety Care: Detect if an elderly person falls or if strangers break in.
  • Smart Home Automation: Automatically turn on lights when someone arrives home, turn off when no one is present.

Key Strengths & Highlights

The biggest advantage is completely camera-free, eliminating privacy leakage risks. Secondly, the cost is extremely low, built with ESP32 modules costing tens of dollars. All data is processed locally, not uploaded to the cloud, with fast response times.

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Getting Started Requirements

High threshold. Requires purchasing specific ESP32 hardware models (e.g., ESP32-S3) and possessing programming and hardware debugging skills. Currently in Beta phase, may require external devices like Cognitum Seed for best results.

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Purpose

Suitable for privacy-preserving vital sign monitoring and home security scenarios. Not suitable for users seeking plug-and-play solutions without hardware debugging experience.

Tech Stack

Project Info

Primary Language
Rust
Default Branch
main
License
MIT
Created
Jun 7, 2025
Last Commit
today
Last Push
today
Indexed
Apr 19, 2026