RuView mmWave Radar Setup
Sets up 60 GHz and 24 GHz mmWave radars for presence, breathing and heart rate sensing.
Install
npx skills add ruvnet/RuView --skill ruview-mmwave -g -a claude-code -y- Repository
- ruvnet/RuView102k
- Category
- Engineering
- Updated
- 3d ago
- License
- MIT
- Context cost
- Lightabout 794 tokens
- Runs scripts
- No, instructions only
What it does
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.
RuView mmWave / FMCW Radar
The radio side-channel: 60 GHz and 24 GHz FMCW radar, standalone and fused with WiFi CSI.
Hardware
| Device | Port | Band | Provides | ~Cost |
|---|---|---|---|---|
| ESP32-C6 + Seeed MR60BHA2 | COM4 (typical) | 60 GHz FMCW | Heart rate, breathing rate, presence | ~$15 |
| HLK-LD2410 | , | 24 GHz FMCW | Presence + distance (gated zones) | ~$3 |
The C6 is RISC-V and can run the radar pipeline; it is not a WiFi-CSI node (use an ESP32-S3 for CSI). LD2410 is a UART module wired to a host or to the C6.
1. Firmware with mmWave fusion (v0.5.0+)
The ESP32 firmware auto-detects an attached MR60BHA2 or LD2410 and emits 48-byte fused vitals records (CSI-derived + radar-derived, reconciled). Binary is ~12 KB larger than the CSI-only build. Build/flash as in ruview-hardware-setup (Windows: Python-subprocess; ESP-IDF v5.4 ≠ Git Bash). Recommended stable firmware tag: v0.5.0-esp32 or later, see docs/user-guide.md release table.
# Provision the radar/fusion node (same provision.py; the firmware probes for the radar on boot)
python firmware/esp32-csi-node/provision.py --port COM8 --ssid "WiFi" --password "secret" --target-ip 192.168.1.20
# Confirm: serial monitor should report which radar was detected and start emitting fused vitals
2. mmWave ↔ WiFi-CSI fusion bridge (host side)
python scripts/mmwave_fusion_bridge.py # bridges radar HR/BR + CSI → unified spatial model
node scripts/passive-radar.js # passive-radar style processing for exploration
The 3D point-cloud demo fuses camera depth (MiDaS) + WiFi CSI + mmWave radar → unified spatial model (~22 ms pipeline, 19K+ pts/frame; ADR-094). Drive it with scripts/mmwave_fusion_bridge.py plus the point-cloud front-end.
