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.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
The radio side-channel: 60 GHz and 24 GHz FMCW radar, standalone and fused with WiFi CSI.
| 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.
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
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.
examples/medical/README.md.| 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 |
README.md, docs/user-guide.md (release table — v0.5.0 mmWave fusion notes, binary sizes)scripts/mmwave_fusion_bridge.py, scripts/passive-radar.jsexamples/medical/README.md (60 GHz mmWave vitals)ruview-verifyまだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
日本語の概要は準備中です。原文の説明を表示しています。
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
日本語の概要は準備中です。原文の説明を表示しています。
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
日本語の概要は準備中です。原文の説明を表示しています。
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
日本語の概要は準備中です。原文の説明を表示しています。
Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
日本語の概要は準備中です。原文の説明を表示しています。
Web browser automation with AI-optimized snapshots for claude-flow agents
日本語の概要は準備中です。原文の説明を表示しています。