ruv
8ff7c2c35a
Add `plugins/ruview` — an end-to-end toolkit for working with RuView (WiFi-DensePose) from Claude Code, mirrored as Codex prompts. Marketplace: `plugins/.claude-plugin/marketplace.json` (one plugin, `ruview`). Skills (9): ruview-quickstart, ruview-hardware-setup, ruview-configure, ruview-applications, ruview-model-training, ruview-advanced-sensing, ruview-cli-api, ruview-mmwave, ruview-verify — shell-first (cargo / python / idf.py / docker / node), no claude-flow MCP dependency. Commands (7): /ruview-start, /ruview-flash, /ruview-provision, /ruview-app, /ruview-train, /ruview-advanced, /ruview-verify. Agents (3): ruview-onboarding-guide, ruview-config-engineer, ruview-training-engineer. Codex mirror: codex/AGENTS.md + codex/README.md + codex/prompts/*.md (full command parity, enforced by scripts/smoke.sh). Docs: docs/adrs/0001-ruview-plugin-contract.md (Proposed). Verification: scripts/smoke.sh (13 structural checks). Provisioning docs reflect the full `provision.py` flag set (TDM mesh, edge tiers, vitals, hop channels, Cognitum Seed, swarm intervals) and the issue #391 NVS-namespace-replace gotcha. Verified: `claude plugin validate` (plugin + marketplace), loads via `claude --plugin-dir`, smoke 13/13, and confirmed against an attached ESP32-S3 on COM8 running the RuView CSI firmware (live adaptive_ctrl + csi_collector serial output). Co-Authored-By: claude-flow <ruv@ruv.net>
4.6 KiB
name, description, allowed-tools
| name | description | allowed-tools |
|---|---|---|
| ruview-advanced-sensing | 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. | Bash Read Write Edit Glob Grep |
RuView Advanced Sensing
The deep end: multistatic mesh, tomography, persistent field models, and the security model that protects them. Most of this lives in wifi-densepose-signal/src/ruvsense/ (14 modules) and wifi-densepose-ruvector/src/viewpoint/ (5 modules).
RuvSense multistatic mode (ADR-029)
Treat every WiFi link in range — including neighbours' APs — as a bistatic radar pair, then fuse them.
Module (signal/src/ruvsense/) |
Purpose |
|---|---|
multiband.rs |
Multi-band CSI frame fusion, cross-channel coherence |
phase_align.rs |
Iterative LO phase-offset estimation, circular mean |
multistatic.rs |
Attention-weighted fusion, geometric diversity |
coherence.rs / coherence_gate.rs |
Z-score coherence scoring; Accept / PredictOnly / Reject / Recalibrate gate decisions |
pose_tracker.rs |
17-keypoint Kalman tracker with AETHER re-ID embeddings |
field_model.rs |
SVD room eigenstructure, perturbation extraction |
tomography.rs |
RF tomography, ISTA L1 solver, voxel grid |
longitudinal.rs |
Welford stats, biomechanics drift detection |
intention.rs |
Pre-movement lead signals (200–500 ms ahead) |
cross_room.rs |
Environment fingerprinting, transition graph |
gesture.rs |
DTW template-matching gesture classifier |
adversarial.rs |
Physically-impossible-signal detection, multi-link consistency |
Cross-viewpoint fusion (ADR-016 viewpoint module)
Combine 2+ nodes geometrically — more nodes, more independent looks, tighter localization.
Module (ruvector/src/viewpoint/) |
Purpose |
|---|---|
attention.rs |
CrossViewpointAttention, GeometricBias, softmax with G_bias |
geometry.rs |
GeometricDiversityIndex, Cramér–Rao bounds, Fisher Information |
coherence.rs |
Phase-phasor coherence, hysteresis gate |
fusion.rs |
MultistaticArray aggregate root, domain events |
Host-side helpers to explore the geometry before deploying: node scripts/mesh-graph-transformer.js, node scripts/passive-radar.js, node scripts/deep-scan.js.
Persistent field model (ADR-030)
field_model.rs builds an SVD eigenstructure of the room and stores it (RVF, ideally on a Cognitum Seed). New CSI frames are projected against it; the residual is the perturbation. Lets you ask "what's different from the empty-room baseline?" and survive restarts.
RF tomography
tomography.rs reconstructs a voxel occupancy grid from the multistatic link set via an ISTA L1 solver (sparse — most voxels are empty). Use with cross-viewpoint geometry for through-wall volumetric imaging. RuVector solver crates back the sparse interpolation (114→56 subcarriers).
Sensing-first RF mode & adaptive mesh kernel
- ADR-031 (RuView sensing-first RF mode), ADR-081 (adaptive CSI mesh firmware kernel), ADR-083 (per-cluster π compute hop), ADR-095/096 (on-ESP32 temporal modeling with sparse GQA attention — runs the temporal head on-device).
Security (ADR-032 — multistatic mesh hardening)
Using neighbours' APs as illuminators and pooling links across a mesh expands the attack surface. Mitigations:
adversarial.rsrejects physically impossible signals and cross-checks multi-link consistency.coherence_gate.rsquarantines low-coherence / suspicious links (Reject / Recalibrate).- Ed25519 witness chain (ADR-028) attests every measurement.
- Run a security review when touching anything on the hardware/network boundary (see
ruview-verifyanddocs/security-audit-wasm-edge-vendor.md).
Validate advanced changes
cd v2 && cargo test --workspace --no-default-features # incl. ruvsense + viewpoint tests
cargo test -p wifi-densepose-signal --no-default-features
cargo test -p wifi-densepose-ruvector --no-default-features
cd .. && python archive/v1/data/proof/verify.py
Reference
- ADRs: 014 (SOTA signal processing), 029 (multistatic mode), 030 (persistent field model), 031 (sensing-first RF), 032 (mesh security hardening), 081/083/095/096
v2/crates/wifi-densepose-signal/src/ruvsense/·v2/crates/wifi-densepose-ruvector/src/viewpoint/docs/research/,docs/security-audit-wasm-edge-vendor.md