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* refactor(train): hoist canonical PCK/OKS to un-gated metrics_core; fold test_metrics onto production (ADR-155 M1 §8) ADR-155 §8 deferred item: test_metrics.rs reference kernels validated production against their OWN reimplementation — a test that cannot catch a canonical-impl bug (both could be wrong the same way). - Extract canonical_torso_size / pck_canonical / oks_canonical / sigmas / bounding_box_diagonal into a new NON-tch-gated `metrics_core` module, so the single metric definition is reachable under `cargo test --no-default-features` (the `metrics` module is tch-gated). `metrics` re-exports every item → still exactly ONE implementation. - Rewrite tests/test_metrics.rs to assert the PRODUCTION pck_canonical / oks_canonical equal hand-computed fixtures (not a reimplementation): canonical_pck_matches_hand_computed_fixture (corr=3/total=4/pck=0.75), hip↔hip normalizer pin, zero-visible⇒0.0, OKS perfect⇒1.0, fake-Gold pin. - Keep an INDEPENDENT raw-threshold reference kernel only as a differential cross-check: test_kernel_agrees_with_canonical asserts it AGREES with canonical where torso==1.0 (genuine cross-check, not duplication). Grade: MEASURED. test_metrics 10→12 tests, 0 failed. Co-Authored-By: claude-flow <ruv@ruv.net> * fix(sensing-server): relabel divergent live PCK/OKS so they're never conflated with canonical (ADR-155 M1 §2.1/§8 Goal C) Goal C named training_api.rs:804 (torso-HEIGHT PCK). Auditing it surfaced TWO findings the ADR-155 §1 table missed: 1. training_api.rs is an ORPHAN file — not declared `mod` in lib.rs OR main.rs, so it does NOT compile into the crate. It does not drive the live server. 2. The REAL live `best_pck`/`best_oks` (main.rs training path → RVF metadata JSON read by model_manager.rs) come from trainer.rs: - `pck_at_threshold` = RAW-threshold PCK, NO torso normalization (the most divergent kind), printed/serialized as bare "PCK@0.2". - `oks_map` calls `oks_single(area=1.0)` = the EXACT fake-Gold pattern ADR-155 §2.1 claimed closed elsewhere — still live here, inflating best_oks. Resolution = RELABEL (torso/raw math is load-bearing on different data; the pub fns can't be renamed without breaking API; sensing-server has no train/ ndarray dep). Honest unify is a tracked §8 backlog item. - training_api.rs: `compute_pck` → `compute_pck_torso_height` + divergence doc; val_pck/best_pck/val_oks struct fields documented as torso-HEIGHT proxies; logs say `pck_torso_h@0.2`. Test torso_pck_is_labelled_distinctly_from_canonical. - trainer.rs (LIVE): `pck_at_threshold` documented raw-unnormalized; `oks_map` area=1.0 flagged fake-Gold; test pck_at_threshold_is_raw_unnormalized_not_canonical. - main.rs: live print relabelled `pck_raw@0.2` / `oks_map(area=1.0 proxy)`. No wire-format field renames (back-compat); no pub-API rename (no silent break). Grade: MEASURED (relabel + divergence pinned). sensing-server 450→451 lib tests, 0 failed. Co-Authored-By: claude-flow <ruv@ruv.net> * docs(adr-155): mark §8 metric items RESOLVED + audit map + honest §1 under-count correction (M1b Goals A/D) - §8.1: full PCK/OKS audit map (every def: file:line, basis, canonical/ legacy/distinct), the two §8 items marked RESOLVED with resolution+why. - Honest finding: §1's "seven divergent metrics" was an UNDER-count — sensing-server's LIVE trainer.rs has a raw-unnormalized PCK and an area=1.0 fake-Gold OKS the table omitted, and the file §8 named (training_api.rs) is orphaned dead code. §9 honest-limits updated. - Goal D: metrics.rs *_v2 variants confirmed caller-less + deprecated; noted for future cleanup, NOT deleted (public API, tch-gated). - CHANGELOG [Unreleased] Fixed entry. Co-Authored-By: claude-flow <ruv@ruv.net> * feat(ruvector): RaBitQ Pass-2 randomized rotation + topk bugfix (ADR-156 §8) Implements the deferred "Multi-bit / Extended RaBitQ Pass 2" backlog item from ADR-156 §8: a deterministic randomized orthogonal rotation applied before sign-quantization, the published RaBitQ construction (Gao & Long, SIGMOD 2024). Rotation construction: Fast Hadamard Transform + seeded ±1 sign flips ("HD" / randomized Hadamard), O(d log d) time and O(d) memory — a dense d×d rotation is O(d²) and infeasible at the 65,535-d the wire format provisions for. Pads to the next power of two; SplitMix64 seeds the sign stream so index-time and query-time rotations are bit-identical. API is additive and backward-compatible: Pass 1 (`from_embedding`) is untouched; Pass 2 is opt-in via `Sketch::from_embedding_rotated` and `SketchBank::with_rotation` (+ `insert_embedding` / `topk_embedding` / `novelty_embedding` helpers that rotate consistently). Default behaviour is unchanged. While building the Pass-2 coverage harness, found and fixed a PRE-EXISTING correctness bug in `SketchBank::topk`: the n>k heap path used `BinaryHeap<Reverse<(d,id)>>` (a min-heap) but treated its peek as the max, so it returned the k FARTHEST sketches as "nearest". The shipped unit tests only exercised the n≤k fast path, so it went unnoticed. Fixed to a plain max-heap; pinned by `topk_heap_path_returns_nearest` and `tight_clusters_give_high_coverage_with_overfetch` (the latter measured 0.072 on the old code). New tests (+17, 100→117 in the crate): rotation determinism/norm-preservation (`rotation_is_deterministic_for_seed`, `rotation_preserves_norm`), Pass-2 shape-compatibility, `pass2_coverage_not_worse_than_pass1`, and a deterministic coverage report. MEASURED top-K coverage (anisotropic planted-cluster fixture, cosine ground truth; dim=128 N=2048 K=8 64 clusters noise=0.35 128 queries): candidate_k=K=8 : Pass1 36.13% -> Pass2 46.39% (both << 90% bar) candidate_k=24 : Pass1 83.89% -> Pass2 91.60% (Pass2 clears 90%) candidate_k=32 : Pass1/Pass2 100% Honest result: rotation consistently helps (+10pp at strict K), but neither pass clears the ADR-084 90% bar at candidate_k==K on this distribution. Pass 2 reaches 90% only with ~3x over-fetch (the ADR-084 "candidate set" deployment pattern). Multi-bit Pass 3 evaluated separately. Co-Authored-By: claude-flow <ruv@ruv.net> * feat(ruvector): multi-bit Pass-3 experiment + ADR-156/084 measured results Adds the multi-bit half of the ADR-156 §8 "Multi-bit / Extended RaBitQ" item as a MEASURED experiment (coverage::measure_multibit): rotate, then b-bit uniform scalar-quantize each coord, rank by L1 over codes — the natural multi-bit generalization of hamming. Measures the bit/coverage tradeoff the backlog item asked for. MEASURED at the strict bar (candidate_k=K=8, anisotropic planted-cluster fixture, cosine ground truth): Pass1 (1-bit, no rot) 36.13% 16 B/vec Pass2 (1-bit, rot) 46.39% 16 B/vec Pass3 (rot, 2-bit) 54.39% 32 B/vec Pass3 (rot, 3-bit) 66.70% 48 B/vec Pass3 (rot, 4-bit) 74.22% 64 B/vec Honest: multi-bit monotonically helps but even 4-bit (4x memory) reaches only 74% at the strict bar — neither rotation nor <=4-bit multi-bit clears the strict-K 90% bar on this distribution. The bar is met via over-fetch (Pass2 @ candidate_k=24). Tests: multibit_tradeoff_report, multibit_1bit_matches_pass2_approx (+ sanity that 1-bit ~= Pass-2). Docs: - ADR-156 §8 item #2 marked RESOLVED-PARTIAL; §5 #2 grade CLAIMED -> MEASURED-on-our-hardware; new §10 with full measured tables, the topk bugfix disclosure, and graded deferred sub-items. - ADR-084: "Pass 2" section answering the rotation open-question with measured numbers + the topk bug note. - CHANGELOG [Unreleased]: Added (Pass-2 milestone) + Fixed (topk heap). Co-Authored-By: claude-flow <ruv@ruv.net>
Architecture Decision Records
This folder contains 45 Architecture Decision Records (ADRs) that document every significant technical choice in the RuView / WiFi-DensePose project.
Why ADRs?
Building a system that turns WiFi signals into human pose estimation involves hundreds of non-obvious decisions: which signal processing algorithms to use, how to bridge ESP32 firmware to a Rust pipeline, whether to run inference on-device or on a server, how to handle multi-person separation with limited subcarriers.
ADRs capture the context, options considered, decision made, and consequences for each of these choices. They serve three purposes:
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Institutional memory — Six months from now, anyone (human or AI) can read why we chose IIR bandpass filters over FIR for vital sign extraction, not just see the code.
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AI-assisted development — When an AI agent works on this codebase, ADRs give it the constraints and rationale it needs to make changes that align with the existing architecture. Without them, AI-generated code tends to drift — reinventing patterns that already exist, contradicting earlier decisions, or optimizing for the wrong tradeoffs.
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Review checkpoints — Each ADR is a reviewable artifact. When a proposed change touches the architecture, the ADR forces the author to articulate tradeoffs before writing code, not after.
ADRs and Domain-Driven Design
The project uses Domain-Driven Design (DDD) to organize code into bounded contexts — each with its own language, types, and responsibilities. ADRs and DDD work together:
- ADRs define boundaries: ADR-029 (RuvSense) established multistatic sensing as a separate bounded context from single-node CSI. ADR-042 (CHCI) defined a new aggregate root for coherent channel imaging.
- DDD models define the language: The RuvSense domain model defines terms like "coherence gate", "dwell time", and "TDM slot" that ADRs reference precisely.
- Together they prevent drift: An AI agent reading ADR-039 knows that edge processing tiers are configured via NVS keys, not compile-time flags — because the ADR says so. The DDD model tells it which aggregate owns that configuration.
How ADRs are structured
Each ADR follows a consistent format:
- Context — What problem or gap prompted this decision
- Decision — What we chose to do and how
- Consequences — What improved, what got harder, and what risks remain
- References — Related ADRs, papers, and code paths
Statuses: Proposed (under discussion), Accepted (approved and/or implemented), Superseded (replaced by a later ADR).
ADR Index
Hardware and firmware
| ADR | Title | Status |
|---|---|---|
| ADR-012 | ESP32 CSI Sensor Mesh for Distributed Sensing | Accepted (partial) |
| ADR-018 | ESP32 Development Implementation Path | Proposed |
| ADR-028 | ESP32 Capability Audit and Witness Record | Accepted |
| ADR-029 | RuvSense Multistatic Sensing Mode (TDM, channel hopping) | Proposed |
| ADR-032 | Multistatic Mesh Security Hardening | Accepted |
| ADR-039 | ESP32-S3 Edge Intelligence Pipeline (on-device vitals) | Accepted (hardware-validated) |
| ADR-040 | WASM Programmable Sensing (Tier 3) | Accepted |
| ADR-041 | WASM Module Collection (65 edge modules) | Accepted (hardware-validated) |
| ADR-044 | Provisioning Tool Enhancements | Proposed |
| ADR-110 | ESP32-C6 firmware extension — Wi-Fi 6 / 802.15.4 / TWT / LP-core | Accepted, P1-P10 complete, firmware-side substrate closed at v0.7.0-esp32. Companion docs: WITNESS-LOG-110 (13 §A0.x entries · 99.56 % cross-board RX · 104.1 µs smoothed sync stdev · ≤100 µs target met), ADR-110-REVIEW-GUIDE (one-page reviewer tour), ADR-110-BRANCH-STATE (coordination map vs feat/adr-115-ha-mqtt-matter). Host decoders + tests: Python SyncPacketParser (10) + Rust wifi_densepose_hardware::SyncPacket (15), cross-language hex pin gates drift. |
Signal processing and sensing
| ADR | Title | Status |
|---|---|---|
| ADR-013 | Feature-Level Sensing on Commodity Gear | Accepted |
| ADR-014 | SOTA Signal Processing Algorithms | Accepted |
| ADR-021 | Vital Sign Detection (breathing, heart rate) | Partial |
| ADR-030 | Persistent Field Model and Drift Detection | Proposed |
| ADR-033 | CRV Signal Line Sensing Integration | Proposed |
| ADR-037 | Multi-Person Pose Detection from Single ESP32 | Proposed |
| ADR-042 | Coherent Human Channel Imaging (beyond CSI) | Proposed |
| ADR-134 | First-Class Channel Impulse Response (CIR) Support | Proposed |
| ADR-135 | Empty-Room Baseline Calibration (per-subcarrier Welford statistics) | Proposed |
Machine learning and training
| ADR | Title | Status |
|---|---|---|
| ADR-005 | SONA Self-Learning for Pose Estimation | Partial |
| ADR-006 | GNN-Enhanced CSI Pattern Recognition | Partial |
| ADR-015 | Public Dataset Strategy (MM-Fi, Wi-Pose) | Accepted |
| ADR-016 | RuVector Training Pipeline Integration | Accepted |
| ADR-017 | RuVector Signal + MAT Integration | Proposed |
| ADR-020 | Migrate AI Inference to Rust (ONNX Runtime) | Accepted |
| ADR-023 | Trained DensePose Model with RuVector Pipeline | Proposed |
| ADR-024 | Project AETHER: Contrastive CSI Embeddings | Required |
| ADR-027 | Project MERIDIAN: Cross-Environment Generalization | Proposed |
| ADR-149 | AetherArena: public spatial-intelligence benchmark on Hugging Face | Proposed |
| ADR-150 | RF Foundation Encoder: pose-preserving, subject/room/device-invariant CSI embedding | Proposed |
| ADR-151 | Per-Room Calibration & Specialized Model Training (room-first → bank of small ruVector specialists) | Proposed |
| ADR-152 | WiFi-Pose SOTA 2026 Intake: geometry-conditioned calibration, external benchmarks, foundation-encoder recipe | Proposed |
Platform and UI
| ADR | Title | Status |
|---|---|---|
| ADR-019 | Sensing-Only UI with Gaussian Splats | Accepted |
| ADR-022 | Windows WiFi Enhanced Fidelity (multi-BSSID) | Partial |
| ADR-025 | macOS CoreWLAN WiFi Sensing | Proposed |
| ADR-031 | RuView Sensing-First RF Mode | Proposed |
| ADR-034 | Expo React Native Mobile App | Accepted |
| ADR-035 | Live Sensing UI Accuracy and Data Transparency | Accepted |
| ADR-036 | Training Pipeline UI Integration | Proposed |
| ADR-043 | Sensing Server UI API Completion (14 endpoints) | Accepted |
| ADR-115 | Home Assistant integration via MQTT auto-discovery + Matter bridge (HA-DISCO + HA-FABRIC + HA-MIND) | Accepted (MQTT track) / Proposed (Matter SDK P8b) |
| ADR-169 | adam-mode — light theme toggle for the three.js realtime demo | Proposed |
| ADR-170 | yoga-mode — yoga pose detection, classification, and scoring for the three.js realtime demo | Proposed |
Architecture and infrastructure
| ADR | Title | Status |
|---|---|---|
| ADR-001 | WiFi-Mat Disaster Detection Architecture | Accepted |
| ADR-002 | RuVector RVF Integration Strategy | Superseded |
| ADR-003 | RVF Cognitive Containers for CSI | Proposed |
| ADR-004 | HNSW Vector Search for Fingerprinting | Partial |
| ADR-007 | Post-Quantum Cryptography for Sensing | Proposed |
| ADR-008 | Distributed Consensus for Multi-AP | Proposed |
| ADR-009 | RVF WASM Runtime for Edge Deployment | Proposed |
| ADR-010 | Witness Chains for Audit Trail Integrity | Proposed |
| ADR-011 | Proof-of-Reality and Mock Elimination | Proposed |
| ADR-026 | Survivor Track Lifecycle (MAT crate) | Accepted |
| ADR-038 | Sublinear GOAP for Roadmap Optimization | Proposed |
| ADR-095 | rvCSI — Edge RF Sensing Runtime Platform | Proposed |
| ADR-096 | rvCSI — Crate Topology, the napi-c Shim, and the napi-rs Node Surface | Proposed |
| ADR-097 | Adopt rvCSI as RuView's primary CSI runtime (phased adoption) | Proposed |
| ADR-098 | Evaluate ruvnet/midstream for RuView's CSI / WebSocket / mesh pipeline |
Rejected |
| ADR-099 | Adopt midstream as RuView's real-time introspection + low-latency tap | Proposed |
Related
- DDD Domain Models — Bounded context definitions, aggregate roots, and ubiquitous language
- User Guide — Setup, API reference, and hardware instructions
- Build Guide — Building from source