RuView

개요

RuView는 ESP32 센서를 통해 WiFi 채널 상태 정보(CSI)를 수집하여 벽 너머의 인체 감지, 호흡 및 심박수 모니터링, 자세 추정을 구현합니다. 완전히 엣지 디바이스에서 실행되며 클라우드나 인터넷이 필요 없습니다.

README 미리보기

# π RuView\n\n\n  \n    \n  \n\n\n> **Beta Software** — Under active development. APIs and firmware may change. Known limitations:\n> - ESP32-C3 and original ESP32 are not supported (single-core, insufficient for CSI DSP)\n> - Single ESP32 deployments have limited spatial resolution — use 2+ nodes or add a [Cognitum Seed](https://cognitum.one) for best results\n> - Camera-free pose accuracy is limited (PCK@20 ≈ 2.5% with proxy labels) — [camera ground-truth training](docs/adr/ADR-079-camera-ground-truth-training.md) targets **35%+ PCK@20**; the pipeline is implemented, but the data-collection and evaluation phases (ADR-079 P7–P9) are still pending, so no measured camera-supervised PCK@20 has been published yet\n>\n> Contributions and bug reports welcome at [Issues](https://github.com/ruvnet/RuView/issues).\n\n## **See through walls with WiFi** ##\n\n**Turn ordinary WiFi into a spatial intelligence / sensing system.** Detect people, measure breathing and heart rate, track movement, and monitor rooms — through walls, in the dark, with no cameras or wearables. Just physics.\n\n### π RuView is a WiFi sensing platform that turns radio signals into spatial intelligence.\n\nEvery WiFi router already fills your space with radio waves. When people move, breathe, or even sit still, they disturb those waves in measurable ways. RuView captures these disturbances using Channel State Information (CSI) from low-cost ESP32 sensors and turns them into actionable data: who's there, what they're doing, and whether they're okay.\n\n**What it senses:**\n- **Presence and occupancy** — detect people through walls, count them, track entries and exits\n- **Vital signs** — breathing rate and heart rate, contactless, while sleeping or sitting\n- **Activity recognition** — walking, sitting, gestures, falls — from temporal CSI patterns\n- **Environment mapping** — RF fingerprinting identifies rooms, detects moved furniture, spots new objects\n- **Sleep quality** — overnight monitoring with slee

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