What is RuView?
RuView is a WiFi sensing platform that analyzes changes in radio signals to infer presence, occupancy, and movement without cameras or wearables. Compatible ESP32 nodes capture Channel State Information for signal processing and experimental breathing and heart-rate estimation. The project also provides model recording, training, and loading workflows.
The system can run locally using Docker or source builds, with a browser-based dashboard and REST and WebSocket interfaces. A simulated mode exercises the pipeline without sensing hardware but does not demonstrate real-world detection. The documentation identifies live pose estimation as below target and unvalidated, labels device-reported vital signs as unvalidated, and distinguishes research benchmarks from deployed sensing capabilities.
Key capabilities
- Presence and motion Processes WiFi signal variation to estimate occupancy and movement, with capabilities dependent on the data source.
- CSI capture Receives measurements from compatible ESP32 sensor nodes for local processing and sensor-mesh workflows.
- Vital-sign processing Provides breathing and heart-rate extraction pipelines whose device-reported results remain unvalidated.
- Visualization and APIs Offers a browser dashboard, REST endpoints, and WebSocket streams for sensing data.
- Model workflows Supports recording CSI data, training models, loading pretrained weights, and adapting models to rooms.
- Edge modules Runs programmable WebAssembly sensing modules directly on compatible ESP32 hardware.
Where RuView fits
RuView fits experimental room-occupancy monitoring, smart-building automation, and WiFi sensing research. Teams can connect sensing outputs to local applications or evaluate the documented Home Assistant MQTT integration. Its camera-free sensing path may suit spaces where collecting video is undesirable, although optional sensor-fusion and supervised-training workflows can use cameras.
Before deployment, teams should verify sensor compatibility, calibration, room-specific performance, and whether outputs come from live hardware or simulation. They should also check API authentication and network source restrictions. Native WiFi modes have narrower capabilities than CSI sensors, and the current sensing server does not provide a Linux RSSI source. Pose and vital-sign outputs require validation before they inform health or safety decisions.
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