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Author	SHA1	Message	Date
Claude	8dfb031cb3	ADR-081: Layer 3 mesh plane + Rust mirror trait — all 5 layers landed ... Fully implements the remaining deferred pieces of the adaptive CSI mesh firmware kernel. All 5 layers (Radio Abstraction, Adaptive Controller, Mesh Sensing Plane, On-device Feature Extraction, Rust handoff) are now implemented and host-tested end-to-end. Layer 3 — Mesh Sensing Plane (firmware/esp32-csi-node/main/rv_mesh.{h,c}): * 4 node roles: Unassigned / Anchor / Observer / FusionRelay / Coordinator * 7 message types: TIME_SYNC, ROLE_ASSIGN, CHANNEL_PLAN, CALIBRATION_START, FEATURE_DELTA, HEALTH, ANOMALY_ALERT * 3 auth classes: None / HMAC-SHA256-session / Ed25519-batch * Payload types: rv_node_status_t (28 B), rv_anomaly_alert_t (28 B), rv_time_sync_t (16 B), rv_role_assign_t (16 B), rv_channel_plan_t (24 B), rv_calibration_start_t (20 B) * 16-byte envelope + payload + IEEE CRC32 trailer * Pure rv_mesh_encode()/rv_mesh_decode() plus typed convenience encoders * rv_mesh_send_health() + rv_mesh_send_anomaly() helpers Controller wiring (adaptive_controller.c): * Slow loop (30 s default) now emits HEALTH * apply_decision() emits ANOMALY_ALERT on transitions to ALERT / DEGRADED * Role + mesh epoch tracked in module state; epoch bumps on role change Layer 5 — Rust mirror (crates/wifi-densepose-hardware/src/radio_ops.rs): * RadioOps trait mirrors rv_radio_ops_t vtable * MockRadio backend for offline tests * MeshHeader / NodeStatus / AnomalyAlert types mirror rv_mesh.h * Byte-identical IEEE CRC32 (poly 0xEDB88320) verified against firmware test vectors (0xCBF43926 for "123456789") * decode_mesh / decode_node_status / decode_anomaly_alert / encode_health * 8 unit tests, including mesh_constants_match_firmware which asserts MESH_MAGIC/VERSION/HEADER_SIZE/MAX_PAYLOAD match rv_mesh.h byte-for-byte * Exported from lib.rs * signal/ruvector/train/mat crates untouched — satisfies ADR-081 portability acceptance test Tests (all passing): test_adaptive_controller: 18/18 (C, decide() 3.2 ns/call) test_rv_feature_state: 15/15 (C, CRC32 87 MB/s) test_rv_mesh: 27/27 (C, roundtrip 1.0 µs) radio_ops::tests (Rust): 8/8 --- total: 68/68 assertions green --- Docs: * ADR-081 status flipped to Accepted * Implementation-status matrix updated; L3 + Rust mirror both marked Implemented * Benchmarks table extended with rv_mesh encode+decode roundtrip * Verification section updated with cargo test invocation * CHANGELOG: two new entries for L3 mesh plane + Rust mirror Remaining follow-ups (Phase 3.5 polish, not blocking): * Mesh RX path (UDP listener + dispatch) on the firmware * Ed25519 signing for CHANNEL_PLAN / CALIBRATION_START * Hardware validation on COM7	2026-04-19 03:57:18 +00:00
Claude	d53e29506e	ADR-081: implement Layers 1/2/4 end-to-end + host tests + QEMU hooks ... Turns the ADR-081 scaffolding into a working adaptive CSI mesh kernel: Layer 1 radio abstraction has an ESP32 binding and a mock binding; Layer 2 adaptive controller runs on FreeRTOS timers; Layer 4 feature-state packet is emitted at 5 Hz by default, replacing raw ADR-018 CSI as the default upstream. New files: firmware/esp32-csi-node/main/adaptive_controller_decide.c (pure policy) firmware/esp32-csi-node/main/rv_radio_ops_mock.c (QEMU binding) firmware/esp32-csi-node/tests/host/Makefile (host tests) firmware/esp32-csi-node/tests/host/test_adaptive_controller.c firmware/esp32-csi-node/tests/host/test_rv_feature_state.c firmware/esp32-csi-node/tests/host/esp_err.h (shim) firmware/esp32-csi-node/tests/host/.gitignore Modified: adaptive_controller.c — includes pure decide.c; emit_feature_state() wired into fast loop (200 ms = 5 Hz) rv_radio_ops_esp32.c — get_health() fills pkt_yield + send_fail csi_collector.{c,h} — pkt_yield/send_fail accessors (ADR-081 L1) rv_feature_state.h — packed size corrected to 60 bytes (was incorrectly 80 in initial commit) main.c — mock binding registered under mock CSI CMakeLists.txt — rv_radio_ops_mock.c under CSI_MOCK_ENABLED scripts/validate_qemu_output.py — 3 new ADR-081 checks (17/18/19) docs/adr/ADR-081-*.md — status → Accepted (partial); implementation-status matrix; measured benchmarks (decide 3.2 ns, CRC32 614 ns); bandwidth 300 B/s @ 5 Hz (99.7% vs raw); verification section CHANGELOG.md — artifact-level entries Tests (host, gcc -O2 -std=c11): test_adaptive_controller: 18/18 pass, decide() = 3.2 ns/call test_rv_feature_state: 15/15 pass, CRC32(56 B) = 614 ns/pkt, 87 MB/s sizeof(rv_feature_state_t) == 60 asserted IEEE CRC32 known vectors verified Deferred (tracked in ADR-081 roadmap Phase 3/4): Layer 3 mesh-plane message types, role-assignment FSM, Rust-side mirror trait in crates/wifi-densepose-hardware/src/radio_ops.rs.	2026-04-19 03:43:08 +00:00
Claude	9648a47fdc	ADR-081: adaptive CSI mesh firmware kernel + scaffolding ... Introduces a 5-layer firmware kernel that reframes the existing ESP32 modules as components of a chipset-agnostic architecture and authorizes adaptive control + a compact feature-state stream as the default upstream. Layers: L1 Radio Abstraction Layer — rv_radio_ops_t vtable + ESP32 binding L2 Adaptive Controller — fast/medium/slow loops (200ms/1s/30s) L3 Mesh Sensing Plane — anchor/observer/relay/coordinator (spec) L4 On-device Feature Extr. — rv_feature_state_t (magic 0xC5110006) L5 Rust handoff — feature_state default; debug raw gated Files: docs/adr/ADR-081-adaptive-csi-mesh-firmware-kernel.md (new) firmware/esp32-csi-node/main/rv_radio_ops.h (new) firmware/esp32-csi-node/main/rv_radio_ops_esp32.c (new) firmware/esp32-csi-node/main/rv_feature_state.{h,c} (new) firmware/esp32-csi-node/main/adaptive_controller.{h,c} (new) firmware/esp32-csi-node/main/main.c (wire L1+L2) firmware/esp32-csi-node/main/CMakeLists.txt (add 4 sources) firmware/esp32-csi-node/main/Kconfig.projbuild (controller knobs) CHANGELOG.md (Unreleased) Default policy is conservative: enable_channel_switch and enable_role_change are off, so behavior matches today's firmware unless an operator opts in via menuconfig. The pure adaptive_controller_decide() is exposed for offline unit tests. Reuses (does not rewrite): csi_collector, edge_processing (ADR-039), swarm_bridge (ADR-066), secure_tdm (ADR-032), wasm_runtime (ADR-040).	2026-04-19 03:14:04 +00:00
ruv	8914538bfe	chore: bump firmware version to 0.6.1 ... Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-16 10:38:02 -04:00
rUv	8a9e890956	Merge pull request #393 from ruvnet/fix/esp32-node-id-clobber ... fix(firmware): defensive node_id capture prevents runtime clobber (#390)	2026-04-16 10:22:59 -04:00
ruv	425f0e6aac	fix(firmware): defensive node_id capture prevents runtime clobber (#390) ... Users on multi-node ESP32 deployments have been reporting for months that their provisioned `node_id` reverts to the Kconfig default of `1` in UDP frames and the `csi_collector` init log, despite boot showing: nvs_config: NVS override: node_id=4 main: ESP32-S3 CSI Node (ADR-018) - Node ID: 4 csi_collector: CSI collection initialized (node_id=1, channel=11) See #232, #375, #385, #386, #390. The root memory-corruption path for the `g_nvs_config.node_id` byte has not been definitively isolated (does not reproduce on my attached ESP32-S3 running current source and the v0.6.0 release binary), but the UDP frame header can be made tamper-proof regardless: 1. `csi_collector_init()` now captures `g_nvs_config.node_id` into a module-local `static uint8_t s_node_id` at init time. 2. `csi_serialize_frame()` reads `buf[4]` from `s_node_id`, not from the global - so any later corruption of `g_nvs_config` cannot affect outgoing CSI frames. 3. All other consumers (`edge_processing.c` x3, `wasm_runtime.c`, `display_ui.c`, `main.c swarm_bridge_init`) now go through a new `csi_collector_get_node_id()` accessor instead of reading the global directly. 4. A canary at end-of-init logs `WARN` if `g_nvs_config.node_id` already diverges from the captured value - this will pinpoint the corruption path if it happens on a user's device. Hardware validation on attached ESP32-S3 (COM8): - NVS loads node_id=2 - Boot log: `main: ... Node ID: 2` - NEW log: `csi_collector: Captured node_id=2 at init (defensive copy for #232/#375/#385/#390)` - Init log: `csi_collector: CSI collection initialized (node_id=2)` - UDP frame byte[4] = 2 (verified via socket sniffer, 15/15 packets) This is defense in depth - it shields the UDP frame from whatever upstream bug is clobbering the struct. When a user hits the original bug, the canary WARN will help isolate the root cause. Refs #232 #375 #385 #386 #390 Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-15 13:47:34 -04:00
rUv	6e015c4626	fix: provision.py esptool v5 + refuse partial NVS flashes (#391) (#392) ... * fix: provision.py esptool v5 syntax + refuse partial NVS flashes (#391) Bug 1: `write_flash` -> `write-flash` for esptool v5.x compat - Actual flash command (flash_nvs, line 153) was already fixed - Dry-run manual-flash hint (line 301) still printed old syntax Bug 2: Refuse partial invocations that would silently wipe NVS - provision.py flashes a fresh NVS binary at offset 0x9000, which REPLACES the entire csi_cfg namespace. Any key not passed on the CLI is erased. - Previously: `provision.py --port COM8 --target-port 5005` would silently wipe ssid, password, target_ip, node_id, etc., causing "Retrying WiFi connection (10/10)" in the field. - Now: refuse unless all of --ssid/--password/--target-ip provided, or --force-partial is set (prints warning listing wiped keys). Validation: - Dry-run: binary generates to 24576 bytes, hint uses write-flash - Safety check: partial invocation rejected with clear message - Force-partial: warning lists keys that will be wiped - Hardware: esptool v5.1.0 `read-flash 0x9000 0x100` works on attached ESP32-S3 (COM8); NVS preserved, device reconnected at 192.168.1.104 with node_id=2 intact after reset. Co-Authored-By: claude-flow <ruv@ruv.net> * docs: CHANGELOG catch-up for v0.5.5, v0.6.0, v0.7.0 (#367) The changelog was stale at v0.5.4 — three releases were cut without updating it. Added full entries for each, plus an [Unreleased] block for the #391 provision.py fixes. version.txt correctly stays at 0.6.0 — v0.7.0 was a model/pipeline release, not a new firmware binary. Latest firmware is v0.6.0-esp32. Closes #367 Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-15 13:12:46 -04:00
rUv	2a05378bd2	Merge pull request #365 from ruvnet/feat/adr-080-qe-remediation ... fix: ADR-080 QE remediation — 13 of 15 issues fixed	2026-04-06 18:40:21 -04:00
ruv	ccb27b280c	merge: bring feat/adr-080-qe-remediation up to date with main ... Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-06 18:36:20 -04:00
ruv	55c5ddfc40	docs: collapse all details sections in README for cleaner view ... Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-06 18:20:30 -04:00
ruv	c5fef33c6a	docs: reorder README sections — v0.7.0 first, then descending ... Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-06 18:18:40 -04:00
ruv	599ea61a17	docs: update README and user guide for v0.7.0 camera-supervised training ... - Add v0.7.0 section with 92.9% PCK@20 result and new scripts - Add camera-supervised training section to user guide with step-by-step - Update release table (v0.7.0 as latest) - Update ADR count (62 → 79) - Update beta notice with camera ground-truth link Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-06 17:52:44 -04:00
rUv	8dddbf941a	Merge pull request #363 from ruvnet/feat/adr-079-camera-ground-truth ... feat: camera ground-truth training pipeline with ruvector optimizations (ADR-079)	2026-04-06 17:29:13 -04:00
ruv	35903a313d	feat: NaN-safe TCN + CSI UDP recorder for real ESP32 training (#362) ... - Add activation clamping [-10, 10] in TCN forward pass to prevent NaN from real CSI amplitude ranges after normalization - Add safe sigmoid with input clamping [-20, 20] - Add scripts/record-csi-udp.py: lightweight ESP32 CSI UDP recorder Validated on real paired data (345 samples): ESP32 CSI: 7,000 frames at 23fps from COM8 Mac camera: 6,470 frames at 22fps via MediaPipe PCK@20: 92.8% | Eval loss: 0.083 | Bone loss: 0.008 Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-06 17:18:41 -04:00
ruv	4bb0b87465	feat: ADR-080 P1+P2 remediation — refactor, perf, tests, safety ... P1 fixes (this sprint): - P1-6: Extract sensing-server modules (cli, types, csi, pose) from main.rs - P1-7: DDA ray march for tomography — O(max(n)) replaces O(n^3) voxel scan - P1-8: Batch neural inference — Tensor::stack/split for single GPU call - P1-10: Eliminate 112KB/frame alloc — islice replaces deque→list copy P2 fixes (this quarter): - P2-11: Python unit tests for 8 modules (rate_limit, auth, error_handler, pose_service, stream_service, hardware_service, health_check, metrics) - P2-13: MAT simulated data safety guard — blocking overlay + pulsing banner - P2-14: Wire token blacklist into auth verification + logout endpoint - P2-15: Frame budget benchmark — confirms pipeline well under 50ms budget Addresses 8 of 10 remaining issues from QE analysis (ADR-080). Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-06 17:01:07 -04:00
ruv	5bd0d59aa6	feat: ADR-080 P1+P2 remediation — refactor, perf, tests, safety ... P1 fixes (this sprint): - P1-6: Extract sensing-server modules (cli, types, csi, pose) from main.rs - P1-7: DDA ray march for tomography — O(max(n)) replaces O(n^3) voxel scan - P1-8: Batch neural inference — Tensor::stack/split for single GPU call - P1-10: Eliminate 112KB/frame alloc — islice replaces deque→list copy P2 fixes (this quarter): - P2-11: Python unit tests for 8 modules (rate_limit, auth, error_handler, pose_service, stream_service, hardware_service, health_check, metrics) - P2-13: MAT simulated data safety guard — blocking overlay + pulsing banner - P2-14: Wire token blacklist into auth verification + logout endpoint - P2-15: Frame budget benchmark — confirms pipeline well under 50ms budget Addresses 8 of 10 remaining issues from QE analysis (ADR-080). Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-06 17:00:27 -04:00
ruv	924c32547e	fix: ADR-080 P0 security + CI remediation from QE analysis ... Address all 5 P0 issues from QE analysis (55/100 score): - P0-1: Rate limiter bypass — validate X-Forwarded-For against trusted proxy list - P0-2: Exception detail leak — generic 500 messages, exception_type gated by dev mode - P0-3: WebSocket JWT in URL (CWE-598) — first-message auth pattern replaces query param - P0-4: Rust tests not in CI — add rust-tests job gating docker-build and notify - P0-5: WebSocket path mismatch — use WS_PATH constant instead of hardcoded /ws/sensing Includes ADR-080 remediation plan and 9 QE reports (4,914 lines). Firmware validated on ESP32-S3 (COM8): CSI collecting, calibration OK. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-06 16:12:13 -04:00
ruv	327d0d13f6	feat: scalable WiFlow model with 4 size presets (#362) ... Add --scale flag with 4 presets for dataset-appropriate sizing: lite: ~190K params, 2 TCN blocks k=3 (trains in seconds) small: ~200K params, 4 TCN blocks k=5 (trains in minutes) medium: ~800K params, 4 TCN blocks k=7 (trains in ~15 min) full: ~7.7M params, 4 TCN blocks k=7 (trains in hours) Refactored model to use dynamic TCN block count, kernel size, channel widths, hidden dim, and SPSA perturbation count — all driven by the scale preset. Default is 'lite' for fast iteration. Validated: lite model completes 30 epochs on 265 samples in ~2 min on Windows CPU (vs stuck at epoch 1 with full model). Scale up with: --scale small|medium|full as dataset grows. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-06 14:55:35 -04:00
ruv	d09baa6a09	fix: remove hardcoded Tailscale IPs and usernames from public files ... - ADR-079: strip SSH user/IP from optimization description - mac-mini-train.sh: replace hardcoded IP with env var WINDOWS_HOST Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-06 14:39:21 -04:00
ruv	486392bb68	docs: update ADR-079 with validated hardware, ruvector optimizations, baseline ... - Status: Proposed → Accepted - Add O6-O10 optimizations (subcarrier selection, attention, Stoer-Wagner min-cut, multi-SPSA, Mac M4 Pro training via Tailscale) - Add validated hardware table (Mac camera, MediaPipe, M4 Pro GPU, Tailscale) - Add baseline benchmark results (PCK@20: 35.3%) - Update implementation plan with completion status Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-06 14:38:40 -04:00
ruv	33f5abd0e0	feat: ruvector + DynamicMinCut optimizations for WiFlow training (#362) ... Add 4 ruvector-inspired optimizations to the training pipeline: - O6: Subcarrier selection (ruvector-solver) — variance-based top-K selection reduces 128→56 subcarriers (56% input reduction) - O7: Attention-weighted subcarriers (ruvector-attention) — motion- correlated weighting amplifies informative channels - O8: Stoer-Wagner min-cut person separation (ruvector-mincut) — identifies person-specific subcarrier clusters via correlation graph partitioning for multi-person training - O9: Multi-SPSA gradient estimation — K=3 perturbations per step reduces gradient variance by sqrt(3) vs single SPSA Also fixes data loader to accept both `kp`/`keypoints` field names and flat CSI arrays with `csi_shape`, and scalar `conf` values. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-06 14:22:08 -04:00
ruv	e3522ddcda	feat: camera ground-truth training pipeline (ADR-079, #362) ... Add 4 scripts for camera-supervised WiFlow pose training: - collect-ground-truth.py: synchronized webcam + CSI capture via MediaPipe PoseLandmarker (17 COCO keypoints at 30fps) - align-ground-truth.js: time-align camera keypoints with CSI windows using binary search, confidence-weighted averaging - train-wiflow-supervised.js: 3-phase supervised training (contrastive pretrain → supervised keypoint regression → bone-constrained refinement) with curriculum learning and CSI augmentation - eval-wiflow.js: PCK@10/20/50, MPJPE, per-joint breakdown, baseline proxy mode for benchmarking Baseline benchmark (proxy poses, no camera supervision): PCK@10: 11.8% | PCK@20: 35.3% | PCK@50: 94.1% | MPJPE: 0.067 Camera pipeline validated over Tailscale to Mac Mini M4 Pro (1920x1080, 14/17 keypoints visible, MediaPipe confidence 0.94-1.0). Target after camera-supervised training: PCK@20 > 50% Closes #362 Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-06 14:07:25 -04:00
ruv	b5e924cd72	fix: embed firmware version from version.txt, log at boot (#354) ... - Add version.txt (0.6.0) read by CMakeLists.txt so esp_app_get_description()->version matches the release tag - Log firmware version on boot: "v0.6.0 — Node ID: X" - Remove stale Kconfig help text (said default 2.0, actual is 15.0) Fixes the version mismatch reported in #354 where flashing v0.5.3 binaries showed v0.4.3 because PROJECT_VER was never set. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-06 11:26:58 -04:00
rUv	854342297a	Merge pull request #359 from ruvnet/docs/hf-links-update ... docs: update HuggingFace links to ruv/ruview	2026-04-03 14:23:17 -04:00
ruv	23b4491e7b	docs: update HuggingFace links to ruv/ruview (primary repo) ... Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 14:23:07 -04:00
rUv	2b24250a69	Merge pull request #358 from ruvnet/feat/deep-scan ... feat: deep-scan.js — comprehensive RF intelligence report	2026-04-03 13:03:28 -04:00
ruv	6d446e5459	feat: deep-scan.js — comprehensive RF intelligence report ... Shows: who, what they're doing, vitals, position, objects, electronics, physics, and RF fingerprint. The 'wow factor' demo script. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 13:03:18 -04:00
rUv	62fd1d96af	Merge pull request #357 from ruvnet/docs/v0.6.0-models-guide ... docs: HuggingFace models + 17 sensing apps + v0.6.0 guide	2026-04-03 10:28:40 -04:00
ruv	b3fd0e2951	docs: add HuggingFace models, 17 sensing apps, v0.6.0 to README + user guide ... README: - New "Pre-Trained Models" section with HuggingFace download link - Model table (safetensors, q4, q2, presence head, LoRA adapters) - Updated benchmarks (0.008ms, 164K emb/s, 51.6% contrastive) - "17 Sensing Applications" section (health, environment, multi-freq) - v0.6.0 in release table as Latest User guide: - "Pre-Trained Models" section with quick start + huggingface-cli - What the models do (presence, fingerprinting, anomaly, activity) - Retraining instructions - "Health & Wellness Applications" section with all 4 health scripts - Medical disclaimer Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 10:28:29 -04:00
rUv	aae01a2be8	Merge pull request #356 from ruvnet/fix/large-dataset-training ... fix: skip triplet JSON export for large datasets (>100K)	2026-04-03 09:37:30 -04:00
ruv	828d0599d7	fix: skip triplet JSON export for large datasets (>100K) ... JSON.stringify fails on 1M+ triplets. Training succeeded (33.3% improvement) but export crashed. Now skips export when >100K triplets. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 09:37:08 -04:00
rUv	21fd7c84e2	Merge pull request #355 from ruvnet/fix/windows-bind-addr ... fix: --bind flag for Windows firewall compatibility	2026-04-03 09:11:01 -04:00
ruv	85417b84a6	fix: add --bind flag for Windows firewall compatibility ... Windows firewall blocks UDP on 0.0.0.0 — must bind to specific WiFi IP. - seed_csi_bridge.py: --bind-addr auto (auto-detects WiFi IP) - rf-scan.js: --bind <ip> option (default 0.0.0.0, use 192.168.1.x on Windows) Confirmed: 195 frames received from both ESP32 nodes with --bind 192.168.1.20 Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 09:09:53 -04:00
rUv	430243c32c	Merge pull request #310 from orbisai0security/fix-v002-display-buffer-uaf ... fix: remove unsafe exec() in display_task.c	2026-04-03 09:01:41 -04:00
ruv	b7650b5243	feat(server): accuracy sprint 001 — Kalman tracker, multi-node fusion, eigenvalue counting ... Original work by @taylorjdawson (PR #341). Merged with v0.5.5 firmware preserved (ADR-069 feature vectors, ADR-073 channel hopping, batch-limited watchdog from #266 fix). New server features: - Kalman tracker bridge for temporal smoothing - Multi-node CSI fusion with field model - Eigenvalue-based person counting - Calibration endpoints (start/stop/status) - Node positions parsing - Adaptive classifier enhancements Co-Authored-By: taylorjdawson <taylor@users.noreply.github.com> Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 08:59:17 -04:00
ruv	4fc491dea5	feat: ADR-078 — 5 multi-frequency mesh applications ... RF tomography (2D backprojection imaging), passive bistatic radar (neighbor APs as illuminators), frequency-selective material classification (metal/water/wood/glass), through-wall motion detection (per-channel penetration weighting), device fingerprinting (RF emission signatures per SSID) All impossible with single-channel WiFi — require 6-channel hopping. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 08:52:50 -04:00
ruv	4f6780f884	feat: ADR-077 — 6 novel RF sensing applications ... Sleep monitor (hypnogram + efficiency), apnea detector (AHI scoring), stress monitor (HRV + LF/HF via FFT), gait analyzer (cadence + tremor), material detector (null pattern classification), room fingerprint (k-means clustering + anomaly scoring) All validated on overnight data (113K frames). Pure Node.js, zero deps. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 08:50:48 -04:00
ruv	085af0c2be	docs: update quick start with 3 deployment options ... Option 1: Docker (simulated, no hardware) Option 2: ESP32 live sensing ($9) Option 3: Full system with Cognitum Seed ($140) Also shows RF scan, SNN, and MinCut commands for v0.5.5 capabilities. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 08:47:31 -04:00
ruv	f4e636aaa2	docs: refocus README introduction on WiFi sensing ... WiFi sensing (presence, vitals, activity, sleep, environment) is now the primary narrative. Pose estimation repositioned as an advanced capability. Highlights: multi-frequency mesh, SNN adaptation, witness chain, Cognitum Seed integration. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 08:45:30 -04:00
ruv	582d51aed6	docs: fix Cognitum Seed pricing — $131 (not $15) ... Updated all BOM references: ESP32 $9 + Cognitum Seed $131 = $140 total Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 08:44:22 -04:00
ruv	b31efe5e92	docs: improve README benchmarks — results-focused with context ... Replace dry metric table with human-readable results that explain why each number matters. 14 benchmarks with real-world significance. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 08:42:52 -04:00
ruv	f03b484dd1	docs: update README limitations — remove 2 resolved items ... Removed: - "No pre-trained model weights" — weights now published (v0.5.4+) - "Multi-person counting overcounts #348" — fixed by MinCut (ADR-075) Added: - Camera-free pose accuracy limitation (2.5% PCK@20, honest about it) Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 08:32:04 -04:00
ruv	7a75277d58	chore: add data/ and models/ to .gitignore ... Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 08:22:29 -04:00
ruv	73ce72d39c	docs: update README with v0.5.5 capabilities and benchmarks ... - New "What's New in v0.5.5" section: SNN, MinCut (#348 fix), CNN spectrogram, WiFlow, multi-frequency mesh, graph transformer - Before/after comparison table (person counting, channels, model) - 15 new script commands with usage examples - Release table updated with v0.5.5 as Latest - v0.5.4 section collapsed (not open by default) Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 08:16:23 -04:00
rUv	4e9e92d713	feat: ADR-074/075/076 — SNN + MinCut + CNN Spectrogram (ruvector advanced sensing) ... feat: ADR-074/075/076 — SNN + MinCut + CNN Spectrogram (ruvector advanced sensing)	2026-04-03 08:00:07 -04:00
ruv	28368b2c70	feat: ADR-076 CNN spectrogram embeddings + graph transformer fusion ... CSI-as-image: 64x20 subcarrier×time matrix → 224x224 → CNN → 128-dim embedding. Same-node similarity 0.95+, cross-node 0.6-0.8. - csi-spectrogram.js: WASM CNN embedding, ASCII visualization, Seed ingest - mesh-graph-transformer.js: GATv2 multi-head attention over ESP32 mesh, fuses multi-node features, generalizes to 3+ nodes Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 00:36:38 -04:00
ruv	4bb8c3303f	feat: ADR-075 min-cut person separation — fixes #348 ... Stoer-Wagner min-cut on subcarrier correlation graph replaces broken threshold-based person counting (was always 4, now correct). Validated: 24/24 windows correctly report 1 person on test data where old firmware reported 4. Pure JS, <5ms per window. - mincut-person-counter.js: live UDP + JSONL replay, overrides vitals - csi-graph-visualizer.js: ASCII spectrum + correlation heatmap - ADR-075: algorithm, comparison, migration path Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 00:34:57 -04:00
ruv	b9778c5ad2	feat: ADR-074 spiking neural network for real-time CSI sensing ... 128→64→8 SNN with STDP online learning — adapts to room in <30s without labels. Event-driven: 16-160x less compute than FC encoder. - snn-csi-processor.js: live UDP with ASCII visualization, EWMA - ADR-073 updated with SNN integration for multi-channel fusion - Fixed magic number parsing to use ADR-018 format (0xC5110001) Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 00:34:31 -04:00
ruv	b6c032d665	docs: add multi-frequency mesh + RF scanner to README ... New capabilities: 6-channel hopping, neighbor APs as passive radar, real-time RF spectrum visualization with null/reflector/movement detection Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 00:26:48 -04:00
ruv	9d70d621da	feat: ADR-073 enable multi-frequency channel hopping from NVS ... - main.c: call csi_collector_set_hop_table() at boot when hop_count > 1 - provision.py: add --hop-channels and --hop-dwell flags, write chan_list blob and dwell_ms to NVS matching firmware's expected format - Validated: Node 1 hopping ch 1/6/11, Node 2 hopping ch 3/5/9, 200ms dwell, null subcarriers reduced from 19% to 16% Co-Authored-By: claude-flow <ruv@ruv.net>	2026-04-03 00:26:22 -04:00