How do I install the Ruview Mmwave skill?

Run npx skillmds@latest add ruvnet/ruview-mmwave in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Ruview Mmwave safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Ruview Mmwave?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Ruview Mmwave free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Ruview Mmwave?

ruvnet (@ruvnet) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Ruview Mmwave by ruvnet — Agent Skill

Name: Ruview Mmwave
Rating: 4.2 (5 reviews)
Author: ruvnet

Ruview Mmwave

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.

ruvnet 84018df 3.7 KB Updated Sep 9, 2026

File contents

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.

3. Standalone radar use

MR60BHA2 (60 GHz) — best for contactless vitals on a (near-)stationary subject: blood pressure proxy, heart rate, breathing rate; $15 hardware, no wearable. See examples/medical/README.md.
LD2410 (24 GHz) — best for cheap presence + coarse distance / gated zones; complements CSI presence (PIR-style fusion) for higher confidence.

4. When to use mmWave vs. WiFi CSI

Situation	Prefer
Contactless vitals, subject stationary, line of sight	MR60BHA2 (cleaner HR/BR than CSI alone)
Cheap, robust presence / occupancy in a defined zone	LD2410 (or LD2410 + CSI)
Through-wall presence / activity, no line of sight	WiFi CSI (mmWave doesn't penetrate walls)
Pose / skeletons	WiFi CSI (WiFlow) — mmWave doesn't do this here
Highest-confidence vitals	Fusion — 48-byte fused vitals reconcile CSI + radar
Volumetric 3D	Fusion — camera depth + CSI + mmWave point cloud

Reference

Hardware tables: README.md, docs/user-guide.md (release table — v0.5.0 mmWave fusion notes, binary sizes)
scripts/mmwave_fusion_bridge.py, scripts/passive-radar.js
examples/medical/README.md (60 GHz mmWave vitals)
ADR-094 (point-cloud GitHub Pages deployment)
Validate firmware changes with the QEMU helpers and ruview-verify

Source: ruvnet/RuView → plugins/ruview/skills/ruview-mmwave/SKILL.md

---name: ruview-mmwavedescription: 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. ```bash # 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) ```bash 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. ## 3. Standalone radar use - **MR60BHA2 (60 GHz)** — best for contactless vitals on a (near-)stationary subject: blood pressure proxy, heart rate, breathing rate; $15 hardware, no wearable. See `examples/medical/README.md`. - **LD2410 (24 GHz)** — best for cheap presence + coarse distance / gated zones; complements CSI presence (PIR-style fusion) for higher confidence. ## 4. When to use mmWave vs. WiFi CSI | Situation | Prefer | |-----------|--------| | Contactless vitals, subject stationary, line of sight | **MR60BHA2** (cleaner HR/BR than CSI alone) | | Cheap, robust presence / occupancy in a defined zone | **LD2410** (or LD2410 + CSI) | | Through-wall presence / activity, no line of sight | **WiFi CSI** (mmWave doesn't penetrate walls) | | Pose / skeletons | **WiFi CSI** (WiFlow) — mmWave doesn't do this here | | Highest-confidence vitals | **Fusion** — 48-byte fused vitals reconcile CSI + radar | | Volumetric 3D | **Fusion** — camera depth + CSI + mmWave point cloud | ## Reference - Hardware tables: `README.md`, `docs/user-guide.md` (release table — v0.5.0 mmWave fusion notes, binary sizes) - `scripts/mmwave_fusion_bridge.py`, `scripts/passive-radar.js` - `examples/medical/README.md` (60 GHz mmWave vitals) - ADR-094 (point-cloud GitHub Pages deployment) - Validate firmware changes with the QEMU helpers and `ruview-verify` --- **Source:** [`ruvnet/RuView`](https://github.com/ruvnet/RuView) → `plugins/ruview/skills/ruview-mmwave/SKILL.md`

Frequently asked questions