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Author SHA1 Message Date
rUv cfd0ad76cf security(core,cli): pin CSI-deserialiser DoS-resistance + ADR-172 (clean-with-evidence) (#1091) 
* test(core,cli): pin DoS-resistance of CSI deserialisers (ADR-127 security review)

Beyond-SOTA security review of wifi-densepose-core + wifi-densepose-cli.
Load-bearing-question verdict: the NaN-state-poisoning bug class does NOT
originate in core — core exposes no stateful accumulator (no Welford,
von-Mises, IIR, voxel grid, running mean); each downstream crate rolls its
own, so each fix is correctly local. Both crates confirmed clean on every
reviewed dimension (panic-on-adversarial-input, NaN handling, unbounded
memory, path traversal, secrets) — no production code changed.

Adds 4 regression pins locking in two existing-but-untested DoS guards:
- core: from_canonical_bytes shape guard (Vec::with_capacity bound) — proven
  to fail with `capacity overflow` when the saturating-mul guard is removed.
- core: canonical decoder never panics on arbitrary/truncated bytes.
- cli: parse_csi_packet rejects an oversized n_antennas*n_subcarriers claim
  before Array2 allocation (33 MB claim in a 2 KB datagram -> None).
- cli: parse_csi_packet never panics on arbitrary UDP bytes.

core: 35 -> 37 lib tests; cli: 24 -> 26 tests; 0 failed. Python proof
unchanged (f8e76f21…46f7a — off the signal path).

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs(adr): ADR-172 — wifi-densepose-cli + core CSI-deserialiser security review

Records the clean-with-evidence verdict + 4 DoS-resistance regression pins
(test-only, committed in a1051607d). Documents the load-bearing finding:
the NaN-state-poisoning bug class does NOT originate in a shared core
primitive (core exposes no stateful accumulator — MEASURED via grep), so
the 3 prior downstream-local fixes are complete. Gives the wifi-densepose-cli
review its own ADR slot (core portion cross-refs ADR-127 §9).

Co-Authored-By: claude-flow <ruv@ruv.net>
 2026-06-14 23:58:09 -04:00
ruv 53b327e649 release: bump signal 0.3.4 / sensing-server 0.3.3 / cli 0.3.1 (fixes #1009, #1004) 
HE20 calibration baseline fix (signal), sensing-server --source auto simulate-latch
fix (sensing-server), HE20 calibrate parser/asserts (cli). See PR #1038.

Co-Authored-By: claude-flow <ruv@ruv.net>
 2026-06-12 16:55:27 -04:00
ruv a27ee6f6cd fix(csi-ingest): real HE20 CSI no longer dropped or replaced with simulated data (#1009, #1004) 
Two ingest bugs caused real ESP32-C6 HE20 CSI to be silently discarded or
never received — the "real data silently lost" failure class. Each fix is
pinned by a test that fails on the old code.

#1009 §1b — HE20 baseline recorder trimmed 256->242 bins by sequential index.
ESP-IDF v5.5.2 delivers all 256 FFT bins for an HE20 frame, but
CalibrationConfig::he20() carried num_active: 242, so the recorder (no HE20
tone map — extract_first_stream takes the first num_active columns
sequentially) kept bins 0..242 = the lower guard band + DC, NOT the 242 active
tones, silently corrupting the empty-room baseline. Now num_active: 256 records
every delivered bin, aligned 1:1 with the live deviation() path. The exact-242
tone map stays only in cir.rs (HE20_ACTIVE), where the Phi sensing matrix needs
it. HE20 synthetic/bench fixtures updated to feed 256-bin frames.

#1009 §1a/§1c — u8->u16 n_subcarriers truncation, regression-pinned.
The ADR-018 wire format carries n_subcarriers as u16 LE at bytes 6-7; a 256-bin
HE20 frame (byte6=0x00) read as one byte decodes to 0 subcarriers -> every
frame skipped. The CLI parser and the sensing-server parse_esp32_frame were
already corrected to u16 under #1005/ADR-110; added regression tests that fail
on the old single-byte read so the truncation cannot silently return.

#1004 — --source auto latched on simulate forever, never binding UDP :5005.
A one-shot boot probe resolved the source once; with no CSI flowing at boot
(the normal firmware/server startup race) it served simulated poses for the
whole process and ignored real CSI arriving seconds later (the prior #937 fix
hard-exited instead — equally wrong). New plan_source() state machine: in auto
mode ALWAYS bind the UDP receiver and serve simulated only until the first real
frame, then udp_receiver_task promotes source -> esp32 (mirroring the existing
esp32 -> esp32:offline reversion). simulated_data_task self-suspends once
promoted. Explicit --source simulated stays a hard, UDP-free offline override.

Validation: 3-crate tests 1118 passed / 0 failed; workspace 3166 passed /
0 failed; Python proof VERDICT: PASS (bit-exact, unaffected). cir.rs untouched.

Co-Authored-By: claude-flow <ruv@ruv.net>
 2026-06-12 16:37:55 -04:00
rUv 17471e93ff ADR-152: WiFi-Pose SOTA 2026 intake — WiFlow-STD benchmark, Rust integrations, ADR-153 802.11bf layer, efficiency frontier (#1008) 
* feat(calibration): NodeGeometry transceiver-geometry recording (ADR-152 §2.1.1)

PerceptAlign-motivated geometry capture at enrollment: per-node optional
records (position, antenna orientation, inter-node distances, acquisition
method) — recorded when known, never required. Event-sourced via
EnrollmentEvent::GeometryRecorded (latest recording wins); persisted on
SpecialistBank with serde defaults so pre-ADR-152 bank JSON loads cleanly
(fixture-proven, and geometry-free banks serialize byte-shape-identical
to the old schema); threaded through MultiNodeMixture as data only — the
learned geometry embeddings and algorithmic fusion use are §2.1.2,
deliberately deferred until the ADR-151 P6 LoRA heads exist.

Geometry recorded from now on means banks captured today remain usable
for layout-conditioned training later — you can't retroactively add
geometry to data you didn't record.

8 new tests (3 geometry, 2 anchor, 2 bank, 1 multistatic) + full-loop
extension (2-node geometry, one tape-measured + one unknown, surviving
the bank JSON round-trip the runtime loads from). 50/50 calibration
(both feature configs) + 23 CLI tests green.

Co-Authored-By: RuFlo <ruv@ruv.net>

* feat(training): two-checkerboard camera↔room calibration for ADR-079 labels (ADR-152 §2.1.3)

Defends the camera-supervised pipeline against PerceptAlign's
"coordinate overfitting": MediaPipe keypoints were emitted in raw camera
coordinates with no shared frame and no transceiver-geometry metadata —
the exact label shape that memorizes deployment layout and collapses
cross-layout.

- scripts/calibrate-camera-room.py + calibration_lib.py: OpenCV
  two-checkerboard calibration → versioned bundle JSON (intrinsics,
  camera→room extrinsics, checkerboard spec, transceiver geometry,
  sha256 calibration_id). Intrinsics resolve from file > cache >
  multi-view computation > loud-warning 2-view fallback.
- collect-ground-truth.py --calibration <bundle>: every sample gains
  keypoints_room (unit bearing rays from the camera center in the room
  frame — documented projective alignment; raw image coords preserved
  so training chooses), camera_origin_room, calibration_id, and the
  transceiver geometry stamp. Without the flag, output is byte-identical
  to before (tested) + a one-line ADR-152 warning.

Design finding (recorded for ADR-152): a single planar checkerboard's
corner grid is centrosymmetric — the reversed corner ordering fits a
ghost camera pose with IDENTICAL reprojection error, so per-board flip
disambiguation is mathematically ill-posed. solve_two_board_extrinsics
solves the joint wall+floor set over all 4 flip combinations, where the
minimum is unique — an independent reason the TWO-checkerboard method is
required, beyond what PerceptAlign states.

15 headless pytest tests green (synthetic corners: extrinsics recovery
incl. ghost resolution, bundle round-trip + hash stability, ray
transforms w/ distortion + cross-resolution, no-calibration byte
identity).

Co-Authored-By: RuFlo <ruv@ruv.net>

* feat(benchmarks): WiFlow-STD reproduction harness + measurement (a) results (ADR-152 §2.2)

Shipped checkpoint REFUTED (0.08% PCK@20, wrong keypoint normalization);
6 reproducibility defects documented (broken imports, corrupted dataset
tail with float32-max garbage that NaN-poisons fp16 BatchNorm, unreachable
test phase). After repairs, retraining with upstream defaults reproduces
96.09% PCK@20 full-test / 96.61% corruption-free (published 97.25%) on
RTX 5080. Claims graded MEASURED-EQUIVALENT; 2.23M params + ~0.055 GFLOPs
verified. Third-party code/weights/data stay out of tree (gitignored).

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat: ADR-152 Rust integrations + ADR-153 802.11bf protocol model

- calibration: GeometryEmbedding — 32-slot permutation-invariant NodeGeometry
  featurization for future LoRA-head conditioning (ADR-152 §2.1.2); derived
  SpecialistBank::geometry_embedding() accessor; 59 tests
- train: MaePretrainConfig + patchify/random-mask with UNSW measured recipe
  (80% masking, (30,3) patches; ADR-152 §2.3, arXiv 2511.18792); strict
  no-truncate/no-NaN policy; proptest properties
- train: WiFlowStdModel — tch-gated port of the verified ~96%-PCK@20
  WiFlow-STD architecture (ADR-152 §2.2 beyond-SOTA); ungated param formula
  pinned to 2,225,042; 15/17-keypoint support; 239 crate tests
- hardware: ieee80211bf forward-compatibility protocol model (ADR-153):
  SpecProfile gates, SensingCapabilities negotiation, required ConsentMode,
  session FSM, SensingTransport + SimTransport + OpportunisticCsiBridge;
  full acceptance checklist covered; 156+4 tests
- deps: ruvector bumps per ADR-152 §2.6 survey (mincut/solver 2.0.6,
  attention 2.1.0, gnn 2.2.0); vendor/ruvector synced to a083bd77f
- docs: ADR-153 accepted; ADR-152 §2.2 status, §2.4 amendment, §2.6 added

Workspace: 162 test suites green (--no-default-features); Python proof PASS.
Known pre-existing flake: homecore-api env_empty_falls_back_to_defaults
(unserialized env-var mutation) — untouched, follow-up.

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs: CHANGELOG + CLAUDE.md entries for ADR-152 integrations and ADR-153

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix(train): repair tch-backend bit-rot — gated path compiles and tests run again

Mechanical API refresh against current tch: Vec::from(Tensor) -> try_from
(+ explicit flatten), numel() usize cast, Rem/div ops -> remainder() /
divide_scalar_mode(floor) — the latter fixed a silent true-division bug in
heatmap argmax decoding; clamp(1.0, f64::MAX) -> clamp_min (torch 2.x scalar
overflow panic); petgraph EdgeRef import; missing EvalMetrics and
verify_checkpoint_dir APIs that tests documented. wiflow_std roundtrip test
uses safetensors (.pt _save_parameters roundtrip broken in torch 2.11
Windows). Gated: 349 passed (incl. all 20 wiflow_std); ungated: unchanged.
Known pre-existing: gaussian-heatmap convention mismatch (2 tests), proof
seed race under parallel threads — documented, deliberate follow-ups.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(train): WiFlow-STD PyTorch->tch weight import + numerical parity proof

export_to_safetensors.py maps the retrained checkpoint (295 tensors -> 248
mapped, param sum exactly 2,225,042; num_batches_tracked dropped) into a
tch-loadable safetensors plus a deterministic parity fixture. Gated #[ignore]
integration test loads it strictly and asserts forward-pass agreement:
max abs diff 1.192e-7 on the seed-42 fixture. dump_variable_names test makes
the tch name layout authoritative. Zero architecture discrepancies found.

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix: workflow-review findings — BN gamma init, ThresholdParams serde, init docs

Concurrent validation workflow (2 review lanes + adversarial verification,
13 agents): 5 confirmed findings, 3 refuted. Fixes:
- wiflow_std: pin BatchNorm gamma to 1.0 (tch default draws Uniform(0,1) —
  silently halves activations in from-scratch training; loaded checkpoints
  unaffected, parity re-verified after the change)
- wiflow_std: document the conv-init divergences vs the reference's
  effective kaiming_normal(fan_out) re-init (from-scratch dynamics only)
- ieee80211bf: ThresholdParams deserialization validates via try_from so
  the <=100 invariant holds for untrusted payloads (+ rejection test)

Benchmarks (release, ruvzen): GeometryEmbedding 1.84us/call (542k/s),
MAE tokenization 7.38us/window (135k/s), 802.11bf FSM 8.9M events/s —
nothing suspicious.

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs(adr): ADR-152 §2.1.4 gate resolved — PerceptAlign repo MIT, dataset on HF

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(benchmarks): edge optimization measured + measurement (b) blocked + 92.9% retraction

Edge optimization (ADR-152 optimize track): ONNX Runtime fp32 is the CPU
latency win (3.2 ms/window, ~3.4x faster than torch, parity 2.4e-7); ORT
dynamic int8 reaches 2.44 MB (paper's ~2.2 MB claim plausible only via
conv-capable toolchains; -0.16pt PCK@20, +18% MPJPE, 2x slower); torch
dynamic quant converts 0% of this conv-only model; fp16 halves storage free
but is slower on CPU.

Measurement (b) BLOCKED-ON-DATA: only 1,077 paired ESP32 windows exist
(stop rule <2k). Forensic recheck of the surviving April holdout RETRACTS
the ADR-079 '92.9% PCK@20' figure: constant-output model, absolute (not
torso) threshold, 69 near-static frames — mean predictor scores 100% under
that protocol; torso-PCK@20 is 19.1%. Corroborates PR #535. Stale citations
removed from user-guide, readme-details, ADR-152 §2.1.3; no-citation rule
extended to ADR-079 accuracy claims. Unblock: >=2k-window multi-pose paired
session + torso-PCK re-baseline.

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs(user-guide): corrected camera-supervised collection tutorial

Step 0 CSI-rate check + session-length math (window yield = frames/20 —
the May session's 8x under-delivery was a ~12 Hz CSI rate, not an aligner
bug); two-checkerboard calibration step (ADR-152 §2.1.3); pose-variety and
confidence guidance; torso-normalized PCK + temporal-split + pred-variance
eval protocol (lessons from the 92.9% retraction); scale presets re-keyed
to realistic window counts.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(benchmarks): static PTQ int8 (calibrated) results + overnight capture script

Conv-only static QDQ beats dynamic int8 on accuracy (PCK@20 96.61-96.63%
vs 96.52%, MPJPE +10% vs +18% over fp32) at ~equal size/latency; all-ops
QDQ strictly worse (int8 activations through attention glue). Entropy
calibration verified bit-identical to MinMax on this data. Deployment:
ONNX fp32 for speed (3.2ms), static conv-only QDQ for smallest (2.53MB).

Also: scripts/overnight-empty-capture.py — segmented UDP CSI recorder for
empty-room baselines (no glob collisions, detach-safe).

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(benchmarks): measurement (b) MEASURED — optimization transfer only, mean-pose baseline wins

WiFlow-STD fine-tuned on 2,046 fresh single-room ESP32 paired windows
(temporal 70/15/15, 70->540 adapter, K=17): pretrained-init 65% PCK@20 vs
scratch 0% (optimization transfer) but frozen-trunk ~0% (no feature
transfer), and NOTHING beats the mean-pose baseline (95.9% PCK@20 —
single subject, near-static normalized coords). Honesty gates held: pred
std 0.0113 (non-constant model) but mean-baseline dominance means no
citable CSI->pose capability from this data. ADR-152 open question 1
answered partially; definitive answer needs multi-subject/position data.

Two new aligner findings: heterogeneous csi_shape with silent zero-padding
(~20%), and extractCsiMatrix's transposed shape label (frame-major data,
[nSc, nFrames] label) — fixes pending.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(benchmarks): efficiency sweep MEASURED — half model dominates full reference

Compact WiFlow-STD variants on the same data/split/protocol: half (843,834
params, 0.38x) strictly dominates the 2.23M reference (PCK@20 96.62 vs
96.61, PCK@50 99.47 vs 99.11, MPJPE 0.00898 vs 0.0094) — the published
architecture is over-parameterized for its own benchmark. quarter (338k)
96.05%; tiny (56,290 params, 1/39.5) holds 94.11% — a ~220KB fp32 edge
candidate. In-domain caveats recorded; cross-domain untested.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(train): compact WiFlow-STD presets in Rust + tiny edge artifact (ADR-152)

WiFlowStdConfig gains half()/quarter()/tiny() mirroring the overnight sweep
exactly: TcnGroupsMode (Fixed/Gcd/Depthwise), input_pw_groups, derived
stride schedule and decoder-mid (all default to upstream behavior; legacy
serde JSON unaffected). Param formulas pin to trained ground truth first
try: 843,834 / 338,600 / 56,290; default 2,225,042 pin and 1.192e-7 parity
unchanged. 248 tests green.

Tiny edge artifact (tiny_edge_bench.py): ONNX fp32 = 295 KB, 0.66 ms/win
(~1,500/s CPU), 94.11% PCK@20 (matches sweep clean-test exactly; parity
1.49e-7). Static int8 is a bad trade at this scale (-1.43pt, +19% MPJPE,
-16% size, slower) — recorded as negative result. Export note: width-16
breaks AdaptiveAvgPool((15,1)) TorchScript export; replaced by exact
mean+matmul equivalent, proven by parity.

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix: resolve all 10 confirmed code-review findings (7-angle review, 20/20 verified)

wiflow_std: min_feature_width (default 15) replaces the keypoints->stride
coupling — for_keypoints(17) now provably builds the trained [2,2,2,2]
graph and pools 15->17, matching the validated Python protocol (pinned by
tests); param_count() total on invalid configs; random_mask returns Result
and rejects non-finite/out-of-range ratios; trainer checkpoints switched
to safetensors (.pt VarStore roundtrip broken on Windows torch 2.11).

ieee80211bf: SBP proxy now re-triggers instances and relays reports via
Action::RelaySbpReport -> SensingFrame::SbpReport (clients consume via
their existing path); missed_instances reset on success = consecutive
semantics; SessionTable gains a guarded SBP entry point + unknown-id drop
counter; initiator-role sessions reject inbound setup/SBP requests
(RejectedNotSupported) closing the idle hijack; StartSetup/StartSbp
outside Idle return InvalidStateForCommand; SBP validation unified
through evaluate_setup with a 1:1 SetupStatus->SbpStatus mapping.
events.rs split out to honor the 500-line cap.

calibration/cli: enrollment geometry now actually reaches trained banks —
both production call sites attach .with_geometry; --geometry flag on
train-room and POST /enroll/geometry + train-body geometry on
calibrate-serve give production a recording surface; geometry-free banks
log the ADR-152 §2.1.2 note.

benchmarks: corruption masks committed as ground truth (unregenerable
after in-place cleaning; verified bit-identical regeneration from the
pristine copy) + generate_corruption_masks.py producer; _bench_common.py
dedups the 5x-copied shim/evaluate/seed/remap (post-refactor PCK@20
re-verified equal to the last digit); remote scripts get the mmap patch;
tiny_edge --calib validated multiple-of-64; onnx_bench --help no longer
executes (and overwrote) the export — artifact restored byte-exact.

Workspace: 2,963 tests passed, 0 failed; Python proof PASS.

Co-Authored-By: claude-flow <ruv@ruv.net>

* ci: build workspace tests without debuginfo — runner disk exhaustion

The combined 38-crate debug target exceeds the GitHub runner's disk
('final link failed: No space left on device'); the same tree measured
151GB locally with full debuginfo. CARGO_PROFILE_{DEV,TEST}_DEBUG=0
shrinks the target ~5-10x; debuginfo serves no purpose in CI test runs.

Co-Authored-By: claude-flow <ruv@ruv.net>
 2026-06-11 17:02:23 -04:00
rUv d0e27e652e fix(firmware): C6 IDF v5.5 guard + HE-LTF host ingest + WITNESS-LOG-110 B1 resolution (#1005) (#1011) 
* fix(firmware): c6_sync_espnow IDF v5.5 send-callback guard + B1 HE-LTF resolution (#1005)

Espressif backported the esp_now_send_cb_t signature change to v5.5
(esp_now_send_info_t = wifi_tx_info_t there), so the #944 guard must be
ESP_IDF_VERSION >= VAL(5,5,0), not MAJOR >= 6.

Validated on this repo's hardware toolchain:
- WITHOUT fix, IDF v5.5.2 esp32c6 build fails with the reporter's exact
  incompatible-pointer error at c6_sync_espnow.c:199 (reproduced)
- WITH fix, clean build on IDF v5.5.2 (esp32c6) AND IDF v5.4 (regression)

Docs: WITNESS-LOG-110 §B1 marked RESOLVED WITH MEASUREMENT (external,
@stuinfla, issue #1005): IDF v5.4 driver downconverts HE->HT; v5.5.2
delivers true HE-LTF (532B / 256 bins / 242 tones, PPDU 0x01 HE-SU).
ADR-110 capability table updated accordingly.

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs: WITNESS-LOG-110 §B1 — in-house HE-LTF replication on the original COM12 C6

84% of 1,525 frames at 532B/PPDU 0x01 (HE-SU) with IDF v5.5.2 + the #1005
guard fix, AP ruv.net 11ax 2.4GHz. Two independent rigs now confirm:
v5.4 downconverts, v5.5.2 delivers 242-tone HE20.

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix(host): 256-bin HE-LTF ingest end-to-end + latent offset bugs (#1005)

Audit of every ADR-018 consumer against live C6 HE20 frames (532B/256-bin):
- sensing-server + CLI calibrate parsers read n_subcarriers from one byte
  (256 decoded as 0) with stale seq/rssi offsets (rssi always 0 — latent,
  pre-existing, confirmed vs firmware csi_collector.c). Fixed to the real
  ADR-018 layout; n_subcarriers u8->u16; byte 18 surfaced as typed PpduType.
- sensing-server probe buffer 256B -> 2048B (532B datagram errored on Windows)
- per-node grid gate: lock densest (n_subcarriers, ppdu_type) grid, re-warm
  on upgrade, skip sparser minority frames — HT-64 never mixes into an
  HE-256 baseline window
- hardware parser: HE-aware bandwidth classification (256-FFT HE20 = 20MHz,
  was Bw160); PpduType/Adr018Flags re-exported
- verbatim live frames (532B HE-SU, 148B HT) embedded as regression fixtures
- archive python parser: bandwidth heuristic mirror fix

Live-validated: calibrate --tier he20 consumed 600x 256-bin frames into an
ADR-135 He20 baseline (242 tones) skipping 94 HT frames; sensing-server
shows node 12 active with real RSSI (-40dBm). 765 tests green across the
three crates; workspace check clean; Python proof PASS.

Co-Authored-By: claude-flow <ruv@ruv.net>

* test(fuzz): esp_netif/ping_sock/ip_addr stubs — un-break ADR-061 fuzz build after #954

csi_collector.c gained esp_netif.h / ping/ping_sock.h / lwip/ip_addr.h
includes for the #954 gateway self-ping; the host-fuzz stub env lacked
them, breaking the fuzz build on main since 5789351b7. Stubs return
no-gateway so the self-ping path early-outs (compiles + links, never
exercised — matches the fuzz threat model which targets frame
serialization, not the network stack).

Co-Authored-By: claude-flow <ruv@ruv.net>
 2026-06-11 11:00:37 -04:00
rUv 2a307138f2 feat: per-room calibration system (ADR-151) + cognitum-v0 appliance integration spec (#989) 
* docs(adr): ADR-151 — Per-Room Calibration & Specialized Model Training

Room-first calibration -> bank of small specialised ruVector models
(breathing, heartbeat, restlessness, posture, presence, anomaly) distilled
from the frozen Hugging-Face-published RF Foundation Encoder (ADR-150).

Four-stage local-first pipeline: baseline (ADR-135 environmental fingerprint)
-> guided enrollment (NEW EnrollmentProtocol, clean anchors not hours) ->
feature extraction (reuse signal_features + ruvsense) -> specialist bank
training (rapid_adapt LoRA heads, RVF storage, HNSW prototypes).

Invariants: specialisation over scale; local heads over a shared public base;
honest STALE degradation on baseline drift. Indexes ADR-149/150/151.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(cli): calibration HTTP API for UI-driven baseline capture (ADR-135/151)

Adds `wifi-densepose calibrate-serve` — an Axum HTTP API that wraps the
ADR-135 CalibrationRecorder so a UI (or any client) can drive an empty-room
baseline capture remotely. Stage 1 ("teach the room") of the ADR-151 room
calibration & training pipeline.

A single background task owns the UDP socket (ESP32 0xC511_0001 frames) and
the optional active recorder; HTTP handlers talk to it over an mpsc command
channel and read a shared status snapshot, keeping the &mut recorder
lock-free. CORS permissive so a browser UI can call it.

Endpoints (/api/v1/calibration/*):
  GET  /health      liveness + UDP ingest stats (frames_seen, streaming)
  POST /start       { tier?, duration_s?, room_id?, min_frames? }
  GET  /status      live progress (state, frames, progress, z, eta) — poll for UI
  POST /stop        finalize the current session early
  GET  /result      finalized baseline summary (amp/phase-dispersion averages)
  GET  /baselines   list persisted baseline .bin files

Reuses the existing calibrate.rs ESP32 wire parser (made pub(crate)); honest
abort when <10 frames arrive in the window (e.g. ESP32 not streaming).

Verified end-to-end over loopback: start -> 300 replayed HT20 frames ->
state=complete, 52-subcarrier baseline, phase_dispersion_avg=0.00096
(concentrated/valid), persisted to disk; all 6 endpoints exercised.
CLI: 19 tests pass; crate builds clean.

Co-Authored-By: claude-flow <ruv@ruv.net>

* test(cli): firewall-free CSI UDP relay for local Windows ESP32 testing

Windows Defender blocks inbound LAN UDP to a freshly-built binary without an
admin allow-rule; python.exe is already allowed. This relay binds the public
CSI port and forwards each datagram verbatim to a loopback port where
`calibrate-serve --udp-bind 127.0.0.1 --udp-port 5006` listens (loopback is
firewall-exempt). No admin required.

Validated: ESP32-format 0xC5110001 frames -> :5005 -> relay -> :5006 ->
calibrate-serve -> state=complete, 52-subcarrier baseline,
phase_dispersion_avg=0.00098 (clean). Completes the no-admin live-test path.

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs(changelog): record ADR-151 calibration API (calibrate-serve)

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(calibration): ADR-151 Stages 2–5 — enrollment, extraction, specialist bank, runtime

New crate wifi-densepose-calibration implementing the per-room pipeline beyond
Stage-1 baseline:

- anchor.rs: guided-anchor sequence + event-sourced EnrollmentSession (Stage 2)
- enrollment.rs: AnchorQualityGate + AnchorRecorder — gates anchors against the
  ADR-135 baseline deviation (presence/motion), re-prompts bad captures
- extract.rs: Features + AnchorFeature — autocorrelation periodicity (breathing/
  HR bands), variance/motion (Stage 3)
- specialist.rs: 6 small room-calibrated models — presence (learned threshold),
  posture (nearest-prototype), breathing/heartbeat (band periodicity),
  restlessness (calm/active normalization), anomaly (novelty vs anchors) (Stage 4)
- bank.rs: SpecialistBank — train/persist + baseline-drift STALE invalidation
- runtime.rs: MixtureOfSpecialists — presence short-circuit + anomaly veto +
  stale flagging (Stage 5)

Statistical heads make the pipeline runnable/validatable today; the ADR-150 HF
RF Foundation Encoder backbone is the documented upgrade path. 29 unit tests pass.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(cli): wire ADR-151 enroll / train-room / room-status / room-watch

Integrates the wifi-densepose-calibration crate into the CLI as four
subcommands driving the full Stage 2–5 pipeline against a live ESP32 raw-CSI
stream (edge_tier=0):

- enroll: walks the guided anchor sequence, gates each capture against the
  ADR-135 baseline deviation (re-prompts bad anchors), writes labelled features
- train-room: fits the SpecialistBank from the enrollment, persists JSON
- room-status: prints a trained bank's summary
- room-watch: live mixture-of-specialists readout (presence/posture/breathing/
  heart/restless) over a rolling window, with anomaly veto + STALE flagging

Per-frame scalar is the mean CSI amplitude (carries presence/motion + breathing
modulation). Validated end-to-end on the live ESP32 (COM8, edge_tier=0): the
real parser → feature extraction → runtime detected breathing (~16–31 BPM) on
hardware. Full multi-anchor enrollment accuracy requires the operator to perform
the poses; phase-based breathing extraction is a noted refinement.

48 tests pass (29 calibration + 19 CLI).

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs(adr-151): mark Stages 1–5 implemented; expand CHANGELOG

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix(cli): keep proven mean-amplitude carrier for room features

The max-variance-subcarrier carrier locked onto motion artifacts (not
breathing) and also had an out-of-bounds bug on variable CSI subcarrier
counts. Reverted to the mean-amplitude carrier, which is validated live to
detect breathing. Phase-based extraction on a stable subcarrier remains the
proper higher-SNR refinement (ADR-151 §4).

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(calibration): multistatic fusion of co-located nodes (ADR-029/151)

MultiNodeMixture fuses several co-located nodes (each with its own
room-calibrated SpecialistBank) into one RoomState:
- presence: OR across nodes (any node seeing a person wins)
- posture/breathing/heartbeat: highest-confidence node (best viewpoint)
- restlessness/anomaly: max across nodes
- veto: any node's physically-implausible signal vetoes the room's vitals
  (anti-hallucination, same as single-node runtime) + presence short-circuit
- stale: any node's STALE flag propagates

Same-room multistatic only; cross-room is federation (ADR-105), not fusion.
6 unit tests (presence OR, best-confidence breathing, single-node veto,
staleness). 35 calibration tests pass.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(cli): multistatic room-watch — fuse co-located nodes (ADR-029/151)

`room-watch --node-bank N:path` (repeatable) groups live CSI frames by node_id
and fuses per-node banks via MultiNodeMixture. Validated live on COM8 (node 9,
edge_tier=0): frames grouped + fused end-to-end. True 2-node fusion is covered
by unit tests; a second raw-CSI node is the hardware blocker. 54 tests pass.

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs(integration): calibration → cognitum-v0 appliance integration overview

Detailed cross-repo integration spec for cognitum-one/v0-appliance: data
contracts (CSI wire format, ADR-135 baseline binary, enrollment/bank/RoomState
JSON schemas), calibrate-serve HTTP API, public crate API, Pi5+Hailo tiering,
and a 5-step appliance integration plan. Grounded in the verified cognitum-v0
inventory (aarch64, cargo 1.96, HAILO10H, ruview-vitals-worker:50054).

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix(calibration): address PR review — aarch64 decouple, API auth, path traversal, throttle

Resolves the review on #989:

- **Cross-compile (the appliance blocker):** make wifi-densepose-mat optional
  and feature-gate it (`mat`), so `cargo build -p wifi-densepose-cli
  --no-default-features` excludes the mat→nn→ort(ONNX)→openssl-sys chain.
  Verified: `cargo tree --no-default-features` shows 0 ort/openssl deps →
  calibration cross-compiles clean for the Pi.
- **Security (must-fix before LAN):**
  - `--token` / CALIBRATE_TOKEN bearer-auth middleware on every route; warns if
    bound non-loopback without a token.
  - sanitize client-supplied `room_id` to [A-Za-z0-9_-] (≤64) before it reaches
    the baseline write path — kills the `../` file-write primitive. + test.
- **Perf:** stop locking shared status + cloning SessionStatus on every UDP
  frame — counters/snapshot flush on the 200 ms tick instead (no CPU
  starvation under flood). finalize write moved to async `tokio::fs::write`.
- **Docs:** ADR-151 STALE wording matches the impl (baseline-id change;
  drift-threshold = P6 refinement); integration doc gets the
  `--no-default-features` build + auth/sanitize notes.

35 calibration + 15 CLI tests (no-default) / 20 CLI (default) pass.

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs(worldgraph,worldmodel): add crates.io READMEs

Plain-language overviews + feature lists, comparison tables (symbolic graph vs
predictive occupancy; graph vs grid vs event-log), usage, and technical
details. Adds readme = "README.md" to both manifests so they render on
crates.io on the next release.

Co-Authored-By: claude-flow <ruv@ruv.net>

* release: worldgraph & worldmodel 0.3.1 (READMEs on crates.io)

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs: precise calibration validation scope (capture+API+auth proven; clean enroll→train→infer not yet on-target)

Aligns ADR-151 §7 + the appliance integration doc with the PR #989 scope
clarification: nothing has run a clean baseline → enroll → train → infer on
live CSI; the live breathing read used the stateless head, not a trained bank.
Adds --source-format adr018v6 to the backlog.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(calibrate-serve): live GET /room/state endpoint (mixture over CSI window)

Adds a live RoomState readout over HTTP — the appliance UI's main need. The
ingest task maintains a rolling per-frame scalar window (flushed on the 200 ms
tick, no per-frame lock); the handler loads a bank (resolved as a sanitized
name under output_dir — same path-traversal defense as room_id), runs the
MixtureOfSpecialists over the window, returns RoomState JSON.

Validated live (ESP32-S3 via relay): breathing 14-19 BPM over HTTP; a
bank=../../etc/passwd query is neutralized to 'etcpasswd' (no traversal).

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(calibrate-serve): POST /room/train + fix AnchorLabel JSON to snake_case

- POST /api/v1/room/train: { room_id, baseline_id, anchors[] } → trains a
  SpecialistBank and persists it as <output_dir>/<room_id>.json (path-sanitized),
  readable via /room/state?bank=<room_id>. Completes the HTTP train→infer loop.
- Fix data-contract bug: AnchorLabel serialized as PascalCase variant names
  (serde default) while as_str() + the integration doc used snake_case. Added
  #[serde(rename_all = "snake_case")] so the JSON wire format matches the
  documented contract (empty/stand_still/…). Locked with a roundtrip test.

Validated live (ESP32-S3): POST train (4 anchors → 6 specialists, persisted) →
GET /room/state returns RoomState with the trained presence/restlessness; the
synthetic-vs-real scale mismatch correctly triggers the anomaly veto. 36
calibration tests pass.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(calibrate-serve): live enroll-over-HTTP (POST /enroll/anchor + /enroll/status)

Closes the last HTTP gap — the appliance can now drive the ENTIRE calibration
pipeline over HTTP without the CLI:
  baseline (start/stop) -> enroll/anchor x8 -> room/train -> room/state

- POST /enroll/anchor { room_id, baseline, label, duration_s? }: the ingest task
  loads the baseline (sanitized name under output_dir), captures the anchor for
  the duration against it (AnchorRecorder + per-frame series), runs the quality
  gate, and on completion replies with the verdict + accumulates the AnchorFeature
  in an in-server enrollment map keyed by room_id. Re-prompts on rejection.
- GET /enroll/status?room=<id>: accepted anchors, next, complete.
- POST /room/train now falls back to the in-server enrollment when anchors[] is
  omitted.

Validated live (ESP32-S3): capture baseline -> enroll stand_still (271 frames,
6s) -> gate correctly rejects "no person detected (presence_z 0.90 < 1.50)"
relative to a same-occupancy baseline (a clean empty-room baseline is the
documented on-target prerequisite). Builds clean; CLI tests pass.

Co-Authored-By: claude-flow <ruv@ruv.net>

* test(calibrate-serve): HTTP integration tests for the room/enroll endpoints

Factor the router into build_router() (shared by execute + tests) and add
tower-oneshot integration tests (no network/ingest needed):
- health + descriptor → 200
- POST /room/train persists the bank; GET /room/state → 200; train with no
  anchors/enrollment → 400
- path-traversal: /room/state?bank=../../etc/passwd → 404 (sanitized, never
  reads outside output_dir)
- enroll/status empty; /enroll/anchor with an unknown label → 400

CI regression coverage for the endpoints added this session. 18 CLI tests pass.

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix(mat): make serde non-optional — unblocks `cargo test --workspace --no-default-features`

Making wifi-densepose-mat optional in the CLI (for the aarch64/ort decouple)
exposed a latent feature bug: mat's `api` module compiles unconditionally and
uses serde, but `serde` was an optional dep enabled only via the `api`/`serde`
features. Previously the CLI's *unconditional* mat dependency enabled those
features transitively, so `--workspace --no-default-features` still got serde;
once mat became optional+gated, the workspace build lost it →
`error[E0432]: unresolved import serde` across mat's api/* (CI red).

mat already pulls serde_json + axum unconditionally, so making `serde`
non-optional has no real cost and restores the workspace build. Does NOT affect
the aarch64 CLI build (mat isn't built there at all): verified
`cargo tree -p wifi-densepose-cli --no-default-features` still shows 0
ort/openssl deps, and `cargo test --workspace --no-default-features` compiles
clean.

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs(claude.md): add wifi-densepose-calibration to crate table (pre-merge)

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs(adr): ADR-152 — WiFi-pose SOTA 2026 intake (geometry-conditioned calibration, external benchmarks, encoder recipe)

Records the 2026-06-10 deep-research run (22 sources, 110 claims, 25
adversarially verified: 24 confirmed / 1 refuted) and the decisions it
implies:

- §2.1 ACCEPTED: geometry-condition the ADR-151 calibration system —
  NodeGeometry at enrollment, geometry embeddings for future LoRA heads,
  PerceptAlign-style two-checkerboard camera↔WiFi alignment for the
  ADR-079 supervised path. PerceptAlign (MobiCom'26) names the failure
  mode ("coordinate overfitting") that matches our own ADR-150 cross-
  subject collapse.
- §2.2 ACCEPTED: benchmark protocol vs external "WiFlow-STD (DY2434)"
  (claimed 97.25% PCK@20, Apache-2.0 weights+dataset) with a no-citation
  rule until measured on our 17-keypoint ESP32 eval set. Name collision
  with our internal WiFlow is disambiguated.
- §2.3 ACCEPTED: amend ADR-150 training recipe per UNSW MAE study —
  80% masking, (30,3) patches, data-over-capacity priority (log-linear,
  unsaturated at 1.3M samples).
- §2.4 watch items: IEEE 802.11bf-2025 published 2025-09-26;
  esp_wifi_sensing as external presence baseline (drop-in claim REFUTED
  0-3); ZTECSITool 160MHz/512-subcarrier anchor node (procurement-gated).
- §2.5 NOT adopted: non-WiFi "foundation model" papers; DensePose-UV
  (no 2025-2026 work does UV regression from commodity WiFi).

Every number is evidence-graded CLAIMED vs MEASURED in the source
register. Re-check horizon 2026-12.

Co-Authored-By: RuFlo <ruv@ruv.net>

* test(calibration): full-loop integration test — baseline→enroll→train→infer proven in-process (ADR-151 §7 gap, software half)

Closes the software half of PR #989's headline validation gap: the
complete calibration loop had never run end-to-end anywhere, even
in-process. tests/full_loop.rs (412 lines, deterministic xorshift32
room simulator, HT20/52-subcarrier/20Hz, same fingerprint family as
the ADR-135 roundtrip test) now drives the CLI's exact stage order
through the public API:

  1. baseline  — 600 static frames, zero motion flags post-warmup,
                 calibration_uuid() exactly as the CLI derives it
  2. enroll    — all 8 AnchorLabel::SEQUENCE anchors through
                 AnchorQualityGate::default(), session is_complete()
  3. extract   — AnchorFeature::from_series recovers injected 0.25Hz
                 and 0.125Hz breathing within ±0.04Hz
  4. train     — SpecialistBank::train fits all 6 specialists; JSON
                 round-trip and the runtime consumes the RELOADED bank
  5. infer     — positive: never-enrolled 0.30Hz subject reads present,
                 18±2 BPM; negative: empty window reads absent;
                 degradation: foreign baseline_id flags STALE

Seed-robust (5 seeds), passes with and without default features:
36 unit + 1 integration green.

Validation docs updated (ADR-151 §7 + integration doc §7 matrix): what
remains is strictly the on-target hardware session (real CSI, physically
empty room, operator performing the guided anchors). Three behavioral
findings from building the test are recorded for pre-session triage:
z-band squeeze between baseline motion flagging (z>2.0) and the still-
anchor gate (presence_z≥1.5) — likeliest on-hardware enroll failure;
variance-only PresenceSpecialist missing motionless-person mean shift;
ungated breathing_hz/heart_hz in noise-window embeddings.

Co-Authored-By: RuFlo <ruv@ruv.net>

* fix(calibration): close all four ADR-152 behavioral findings pre-hardware-session

The full-loop integration test surfaced three findings; fixing the third
exposed a fourth. All four are fixed and regression-guarded:

1. z-band squeeze (enrollment.rs) — anchor motion is now measured from
   frame-to-frame deltas of the deviation series (|Δz| > Z_DELTA_MOTION
   0.5 ∨ |Δφ| > π/6), not from the absolute motion_flagged, which fires
   at amplitude_z_median > 2.0 vs the EMPTY baseline and so conflated
   presence strength with motion. A strongly-reflecting still person
   (z = 3.0 — every frame flagged by the old heuristic) now enrolls.
   The old unit tests mocked (z=3.0, motion=false), a combination the
   real deviation() can never emit — which is exactly how the squeeze
   hid; tests now derive the flag from z the way the producer does.

2. variance-only presence (specialist.rs) — PresenceSpecialist gains a
   mean-shift channel: present when variance > threshold OR
   |mean − empty_mean| > mean_dist_threshold (trained at half the
   empty→occupied mean distance, None when the means don't separate).
   Detects the motionless person whose body raises the scalar mean but
   not its variance. Old persisted banks deserialize with the channel
   inert (serde default None) — variance-only behavior preserved,
   proven by a fixture test against pre-change JSON.

3. ungated hz embedding (extract.rs) — Features::embedding() zeroes
   breathing_hz/heart_hz below EMBED_MIN_SCORE (0.25), keeping the
   random in-band peaks of noise windows out of the posture/anomaly
   prototype space. Raw fields stay ungated (specialists have their
   own stricter gates).

4. heart-band lag-floor leakage (extract.rs, found while fixing 3) —
   a pure 0.30 Hz breathing signal scored 0.67 in the heart band at
   3.33 Hz: out-of-band rhythm leaks as a monotonic slope whose max
   sits at the band's lag floor, so score gating alone cannot stop it.
   autocorr_dominant now requires the winning lag to be an interior
   local maximum; band-edge "peaks" are rejected, true in-band peaks
   (interior by definition) are preserved.

full_loop.rs strengthened to drive the fixes end-to-end: the StandStill
anchor is now a z=3.0 strong reflector (unenrollable pre-fix), and a new
motionless-person runtime case proves mean-channel detection at empty-
level variance.

Validation: 41 calibration unit + 1 full-loop integration + 23 CLI tests
green; cargo test --workspace --no-default-features exit 0.

Co-Authored-By: RuFlo <ruv@ruv.net>
 2026-06-10 15:21:09 -04:00
rUv c7ddb2d7d1 feat(worldmodel): ADR-147 — OccWorld world model integration, wifi-densepose-worldmodel v0.3.0 (#856) 
* feat(worldmodel): ADR-147 — OccWorld integration, wifi-densepose-worldmodel v0.3.0 (#854)

- New crate `wifi-densepose-worldmodel` v0.3.0: async Unix-socket bridge
  to OccWorld Python inference server; `OccWorldBridge`, `OccupancyGrid3D`,
  `TrajectoryPrior`, `worldgraph_to_occupancy` encoder (14/14 tests pass)
- `scripts/occworld_server.py`: long-lived Python inference server for
  OccWorld TransVQVAE (72.4M params); applies API-bug patches; dummy mode
  for CI testing; graceful SIGTERM shutdown
- `pose_tracker.rs`: `trajectory_prior` soft-blend injection (80/20
  Kalman/prior) on torso keypoint; `set_trajectory_prior()` public method
- CI: added `Run ADR-147 worldmodel tests` step
- ADR-147: accepted — OccWorld primary (209 ms, 3.37 GB VRAM, RTX 5080);
  Cosmos deferred to ADR-148 (32.54 GB VRAM exceeds hardware)
- Benchmark proof: 208.7 ms P50, 3.37 GB peak VRAM, 12.1 GB headroom

Co-Authored-By: claude-flow <ruv@ruv.net>

* chore: update ruvector.db state

Co-Authored-By: claude-flow <ruv@ruv.net>

* chore: ruvector.db sync

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix(cli): add missing min_frames field to CalibrateArgs test helper

E0063 in calibrate.rs:448 — CalibrateArgs gained min_frames in ADR-135
but the default_args() test helper was not updated. min_frames=0 means
'use tier default', matching the existing runtime behaviour.

Co-Authored-By: claude-flow <ruv@ruv.net>
 2026-05-29 16:53:51 -04:00
ruv 36db13aa7e feat(cli): --min-frames override for low-traffic / debug environments 
Adds a `--min-frames N` flag to `wifi-densepose calibrate` that overrides
the ADR-135 tier minimum (default 600 frames at 20 Hz for HT20).

Motivation: validated end-to-end against a live ESP32-S3 on COM9, freshly
re-provisioned with target-ip = 192.168.1.50 (this host). The firmware
emits CSI at roughly 0.5 Hz in the current quiet RF environment (most
UDP packets are 0xC511_0006 status, not 0xC511_0001 CSI). Waiting 20 min
to collect 600 frames at install time is operator-hostile; raising the
firmware's CSI rate is a separate concern.

When `--min-frames > 0`, the CLI prints a WARN line stating the override
relaxes the phase-concentration guarantee and should not be used in
production. ADR-135 defaults are preserved unchanged.

Live-hardware validation with `--min-frames 10` over 32 s captured 10
real CSI frames from the ESP32, finalised a baseline-real.bin (860 B)
with correct magic 0xCA1B_0001, version 1, tier HT20, and 52 active
subcarriers. End-to-end pipeline confirmed against real hardware, not
just synthetic UDP.

Co-Authored-By: claude-flow <ruv@ruv.net>
 2026-05-28 21:08:28 -04:00
ruv 8504638187 feat(signal): ADR-135 — empty-room baseline calibration 
Operator-initiated calibration that records 30 s of stationary CSI,
emits a per-subcarrier baseline (amplitude mean+variance via Welford,
phase via circular sin/cos sums with von Mises dispersion), and gates
downstream stages on a deviation z-score. Plugs into multistatic
coherence gating, motion/presence detection, and the new ADR-134 CIR
estimator as a reference-subtracted input.

API surface (under wifi_densepose_signal):
  CalibrationConfig::{ht20, ht40, he20, he40}
  CalibrationRecorder { record(), finalize(), frames_recorded() }
  BaselineCalibration {
    subcarriers: Vec<SubcarrierBaseline>,
    deviation(&CsiFrame), subtract_in_place(&mut CsiFrame),
    to_bytes(), from_bytes()
  }
  CalibrationDeviationScore { amplitude_z_median, amplitude_z_max,
                              phase_drift_median, motion_flagged }
  CalibrationError { SubcarrierMismatch, TierMismatch,
                     InsufficientFrames, VersionMismatch, TruncatedBuffer }

Binary baseline format: magic 0xCA1B_0001 + u8 version=1 + u8 tier +
captured_at_unix_s (i64) + frame_count (u64) + num_subcarriers (u32) +
[SubcarrierBaseline; N] as 16 bytes each (amp_mean, amp_variance,
phase_mean, phase_dispersion as f32 LE). Hand-written serialisation so
the format is stable across Rust toolchain versions without serde drift.

CLI: new `wifi-densepose calibrate` subcommand binds a UDP listener
(0xC511_0001 frames), streams them through CalibrationRecorder, prints
a real-time z-score banner per ADR-135 §risk 1 (operator-may-be-moving),
aborts on sustained high deviation, and writes the binary baseline to
disk. Local UDP packet parser duplicated from sensing-server (per ADR
discussion — avoids cross-crate API churn).

Witness: cross-platform-deterministic SHA-256 over the per-subcarrier
quantised baseline profile (u16 LE at 1e-2/1e-4/1e-3, no sort) using
the lesson learnt from the CIR PR #837 libm-jitter fix. Hash:
d6bce07ecb1648e6936561df44bf4a3bfc17bb0ba5f692646b2301d105b52f67

CI guard: new "ADR-135 calibration witness proof (determinism guard)"
step under the Rust Workspace Tests job, adjacent to the existing
ADR-134 CIR guard. Regressions are unambiguously attributable.

Hardware-in-loop validation: full 600-frame capture exercised via the
new scripts/synth-csi-udp.py emitter targeting 127.0.0.1:5005. The CLI
binary received 600 frames at 20 Hz, z_med stable at ~0.7, motion
correctly NOT flagged, finalised baseline written to baseline.bin (860
bytes) with correct magic + version + timestamp in the header. Live
ESP32 capture from COM9 is operator follow-up — requires provisioning
the firmware's UDP target IP to match the host running the CLI.

Test results (cargo test -p wifi-densepose-signal --no-default-features):
  lib:                    382 pass / 0 fail / 1 ignored
  calibration_synthetic:   17 pass / 0 fail
  calibration_drift:        5 pass / 0 fail
  calibration_roundtrip:   10 pass / 0 fail
  cir_*:                    9 pass + 6 documented P2 ignores
  doctest:                 10 pass

Bench: 20 Criterion combinations registered
(recorder_record / recorder_finalize / deviation / record_600 /
to_bytes across HT20/HT40/HE20/HE40 tiers).

Witness: bash scripts/verify-calibration-proof.sh → VERDICT: PASS

Co-Authored-By: claude-flow <ruv@ruv.net>
 2026-05-28 18:57:08 -04:00
rUv 004a63e82d fix(security): audit — fix RUSTSEC vulns, clippy warnings, dead code (#769) 
- Upgrade openssl to 0.10.78 (CVE-2026-41676), jsonwebtoken to 9.4
- Suppress unmaintained-only/no-CVE advisories in .cargo/audit.toml
  with per-entry rationale
- Fix all `cargo clippy --all-targets -- -D warnings` errors across
  35 crates: derivable_impls, needless_range_loop, map_or→is_some_and/
  is_none_or, await_holding_lock (drop MutexGuard before .await),
  ptr_arg (&mut Vec→&mut [T]), useless_conversion, approximate_constant
  (2.718→E, 3.14→PI), field_reassign_with_default, manual_inspect,
  useless_vec, lines_filter_map_ok, print_literal, dead_code
- Apply `cargo fmt --all`
- Pre-existing test failure in wifi-densepose-signal
  (test_estimate_occupancy_noise_only) is not introduced by this PR
 2026-05-23 05:36:13 -04:00
dependabot[bot] a80617ee84 chore(deps): bump console from 0.15.11 to 0.16.3 in /v2 (#471) 
Bumps [console](https://github.com/console-rs/console) from 0.15.11 to 0.16.3.
- [Release notes](https://github.com/console-rs/console/releases)
- [Changelog](https://github.com/console-rs/console/blob/main/CHANGELOG.md)
- [Commits](https://github.com/console-rs/console/compare/0.15.11...0.16.3)

---
updated-dependencies:
- dependency-name: console
  dependency-version: 0.16.3
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
 2026-05-17 18:10:01 -04:00
dependabot[bot] afc86c6fc4 chore(deps): bump thiserror from 1.0.69 to 2.0.18 in /v2 (#469) 
Bumps [thiserror](https://github.com/dtolnay/thiserror) from 1.0.69 to 2.0.18.
- [Release notes](https://github.com/dtolnay/thiserror/releases)
- [Commits](https://github.com/dtolnay/thiserror/compare/1.0.69...2.0.18)

---
updated-dependencies:
- dependency-name: thiserror
  dependency-version: 2.0.18
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
 2026-05-17 18:09:54 -04:00
dependabot[bot] ba370c7b08 chore(deps): bump tabled from 0.15.0 to 0.20.0 in /v2 (#481) 
Bumps [tabled](https://github.com/zhiburt/tabled) from 0.15.0 to 0.20.0.
- [Changelog](https://github.com/zhiburt/tabled/blob/master/CHANGELOG.md)
- [Commits](https://github.com/zhiburt/tabled/commits)

---
updated-dependencies:
- dependency-name: tabled
  dependency-version: 0.20.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
 2026-05-17 18:07:57 -04:00
rUv f49c722764 chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 
The Rust port lived two directories deep (rust-port/wifi-densepose-rs/)
without any sibling under rust-port/ that warranted the extra level.
Move the whole workspace up to v2/ to match v1/ (Python) at the same
depth and shorten every cd / build command across the repo.

git mv preserves history for all tracked files. 60 files updated for
path references (CI workflows, ADRs, docs, scripts, READMEs, internal
.claude-flow state). Two manual fixes for relative-cd paths in
CLAUDE.md and ADR-043 that became wrong after the depth change
(cd ../.. → cd ..).

Validated:
- cargo check --workspace --no-default-features → clean (after target/
  nuke; the gitignored target/ was carried by the OS rename and had
  hard-coded old paths in build scripts)
- cargo test --workspace --no-default-features → 1,539 passed, 0 failed,
  8 ignored (same totals as pre-rename)
- ESP32-S3 on COM7 → still streaming live CSI (cb #40300, RSSI -64 dBm)

After-merge follow-up: contributors should `rm -rf v2/target` once and
let cargo regenerate from the new path.
 2026-04-25 21:28:13 -04:00