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🛠️ Tool
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π RuView is a WiFi sensing platform that converts radio signals into spatial intelligence using Channel State Information (CSI) from ESP32 sensors. The system enables presence detection through walls, vital sign monitoring, activity recognition, and environmental mapping without cameras or cloud dependency.
How It Works
Every WiFi router fills a space with radio waves. When people move, breathe, or sit still, they disturb those waves in measurable ways. RuView captures these disturbances using CSI data from low-cost ESP32 sensors and converts them into actionable spatial intelligence: who is present, what they are doing, and whether they are okay.
Key Capabilities
The platform senses five primary categories:
• Presence and occupancy: detecting people through walls, counting them, tracking entries and exits
• Vital signs: breathing rate and heart rate measured contactlessly during sleep or sitting
• Activity recognition: walking, sitting, gestures, and falls derived from temporal CSI patterns
• Environment mapping: RF fingerprinting to identify rooms, detect moved furniture, and spot new objects
• Sleep quality: overnight monitoring with sleep stage classification and apnea screening
Technical Architecture
The system is built on RuVector and Cognitum Seed. It runs entirely on edge hardware: an ESP32 mesh (approximately $9 per node) paired with a Cognitum Seed for persistent memory, cryptographic attestation, and AI integration. No cloud, no cameras, no internet required.
Spiking neural networks learn each environment locally and adapt in under 30 seconds. Multi-frequency mesh scanning operates across 6 WiFi channels, using neighboring routers as free radar illuminators. Each node ships 21 entities: 11 raw signals plus 10 inferred semantic states including someone-sleeping, possible-distress, room-active, elderly-inactivity-anomaly, meeting-in-progress, bathroom-occupied, fall-risk-elevated, bed-exit, no-movement, and multi-room-transition.
Smart Home Integration
The platform integrates natively with four major ecosystems: Home Assistant via HA-DISCO MQTT publisher (single --mqtt flag), Apple Home and HomePod as a discoverable HAP-1.1 bridge, Google Home and Amazon Alexa via the same Home Assistant bridge or a Matter endpoint. Siri, Google Assistant, and Alexa can voice-report presence and vitals by room with zero custom skills. Three starter Home Assistant Blueprints are included.
Considerations
The edge-only architecture preserves privacy but limits remote access without additional infrastructure. The CSI approach for spatial sensing is well-established in research, and the $9 per node cost makes broad deployment feasible. Performance in dense urban RF environments with many overlapping networks is not well documented. The technique of using neighbor routers as radar illuminators depends on local RF conditions that vary between deployments. Haven't tested personally.
🔹 wifisensing
#esp32 #smarthome #tool #csi
🔗 Source:
https://github.com/ruvnet/ruview
