// Onboarding and first-run for RuView (WiFi-DensePose) — Docker demo with simulated data, repo build, and the fastest path to a live sensing dashboard. Use when someone is new to RuView or wants the shortest path to "it works on my machine".
Advanced RuView capabilities — RuvSense multistatic sensing (attention-weighted fusion, geometric diversity, persistent field model), cross-viewpoint fusion across multiple nodes, RF tomography (ISTA L1 solver, voxel grids), longitudinal biomechanics drift, pre-movement intention signals, adversarial signal detection, and multistatic mesh security hardening. Use for research-grade or multi-node deployments.
Run RuView sensing applications — presence/occupancy, breathing & heart rate, activity & fall detection, 17-keypoint pose estimation (WiFlow), sleep monitoring & apnea screening, environment mapping, Mass Casualty Assessment (MAT), and the 3D point-cloud fusion demo. Use when someone wants to actually *do* something with a working RuView setup.
Use the RuView `wifi-densepose` CLI binary (incl. MAT scan/status/zones/survivors/alerts/export subcommands), the REST API (`wifi-densepose-api`, Axum), and the browser/WASM build (`wifi-densepose-wasm`, `wifi-densepose-wasm-edge`). Use when integrating RuView into another program, scripting it from the shell, exposing it over HTTP, or shipping it to the browser / ESP32-WASM3.
Configure RuView — ESP32 sdkconfig variants, NVS provisioning, WiFi channel / MAC filter overrides (ADR-060), edge intelligence modules (ADR-041), sensing-server flags, multi-node mesh, and Cognitum Seed integration. Use when adjusting how a deployed RuView system behaves without changing code.
ESP32-S3 / ESP32-C6 firmware build, flash, WiFi provisioning, and serial monitoring for RuView CSI sensing nodes. Use when setting up physical hardware, reflashing a node, or debugging a device that isn't streaming CSI.
Set up and run RuView mmWave / FMCW radar sensing — ESP32-C6 + Seeed MR60BHA2 (60 GHz, heart rate / breathing rate / presence) and HLK-LD2410 (24 GHz, presence + distance), plus mmWave↔WiFi-CSI sensor fusion (48-byte fused vitals, MR60BHA2/LD2410 auto-detect, v0.5.0+). Use when the deployment includes a millimetre-wave radar alongside or instead of WiFi CSI.
| name | ruview-quickstart |
| description | Onboarding and first-run for RuView (WiFi-DensePose) — Docker demo with simulated data, repo build, and the fastest path to a live sensing dashboard. Use when someone is new to RuView or wants the shortest path to "it works on my machine". |
| allowed-tools | Bash Read Write Edit Glob Grep |
Get a newcomer from zero to a running RuView sensing dashboard. Three tiers, pick the one that matches the hardware on hand.
docker pull ruvnet/wifi-densepose:latest
docker run -p 3000:3000 ruvnet/wifi-densepose:latest
# open http://localhost:3000 — simulated CSI, full UI
Use this to demo the dashboard, explore the API, or develop UI without a sensor.
# Rust workspace (1,400+ tests, ~2 min)
cd v2
cargo test --workspace --no-default-features
# Single-crate sanity check (no GPU)
cargo check -p wifi-densepose-train --no-default-features
# Python proof (deterministic SHA-256 pipeline check)
cd ..
python archive/v1/data/proof/verify.py # must print VERDICT: PASS
If verify.py fails on a hash mismatch after a numpy/scipy bump:
python archive/v1/data/proof/verify.py --generate-hash
python archive/v1/data/proof/verify.py
This is the real thing. Hand off to the ruview-hardware-setup skill for the flash/provision/monitor loop, then:
# Lightweight sensing server (consumes the ESP32 UDP CSI stream)
cd v2
cargo run -p wifi-densepose-sensing-server
# Live RF room scan / SNN learning helpers:
node ../scripts/rf-scan.js --port 5006
node ../scripts/snn-csi-processor.js --port 5006
ruview-model-training skill, ADR-079).| Goal | Skill / command |
|---|---|
| Flash & provision an ESP32 node | ruview-hardware-setup · /ruview-flash · /ruview-provision |
| Tune channels / MAC filter / edge modules | ruview-configure |
| Run a sensing application (presence, vitals, pose, sleep, MAT) | ruview-applications · /ruview-app |
| Train a pose / sensing model | ruview-model-training · /ruview-train |
| Multistatic mesh, tomography, cross-viewpoint fusion | ruview-advanced-sensing · /ruview-advanced |
| Verify the build + generate a witness bundle | ruview-verify · /ruview-verify |
README.md — feature matrix, hardware table, install optionsdocs/user-guide.md, docs/wifi-mat-user-guide.md, docs/build-guide.md, docs/TROUBLESHOOTING.mddocs/tutorials/, examples/ — runnable examples (environment, medical, sleep, stress, ruview_live.py)