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v0.6.2-esp32

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Release v0.6.2-esp32: ADR-081 kernel + Timer Svc fix, 4MB CI variant

version.txt → 0.6.2.

firmware-ci.yml: matrix-build both 8MB (sdkconfig.defaults) and 4MB
(sdkconfig.defaults.4mb) variants, uploading variant-named artifacts
(esp32-csi-node.bin / esp32-csi-node-4mb.bin, partition-table.bin /
partition-table-4mb.bin). Unblocks 6-binary releases from CI alone,
no local ESP-IDF required.

CHANGELOG: promote [Unreleased] ADR-081 work into [v0.6.2-esp32],
plus Fixed entries for Timer Svc stack overflow and the
fast_loop_cb → emit_feature_state implicit-decl compile error.

Validation: 30 s run on ESP32-S3 (MAC 3c:0f:02:e9:b5:f8), 149
rv_feature_state emissions, no stack overflow, HEALTH mesh packet sent.

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

v0.6.1-esp32

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chore: bump firmware version to 0.6.1

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

v0.7.0

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Merge pull request #363 from ruvnet/feat/adr-079-camera-ground-truth

feat: camera ground-truth training pipeline with ruvector optimizations (ADR-079)

v0.6.0-esp32

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Merge pull request #356 from ruvnet/fix/large-dataset-training

fix: skip triplet JSON export for large datasets (>100K)

v0.5.5-esp32

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feat: ADR-074/075/076 — SNN + MinCut + CNN Spectrogram (ruvector adva…

…nced sensing)

feat: ADR-074/075/076 — SNN + MinCut + CNN Spectrogram (ruvector advanced sensing)

v0.5.4-esp32

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feat: ADR-069 ESP32 CSI → Cognitum Seed RVF pipeline (v0.5.4-esp32)

feat: ADR-069 ESP32 CSI → Cognitum Seed RVF pipeline (v0.5.4-esp32)

v0.5.3-esp32

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feat: cross-node fusion + DynamicMinCut + RSSI tracking (v0.5.3)

* feat(server): cross-node RSSI-weighted feature fusion + benchmarks

Adds fuse_multi_node_features() that combines CSI features across all
active ESP32 nodes using RSSI-based weighting (closer node = higher weight).

Benchmark results (2 ESP32 nodes, 30s, ~1500 frames):

  Metric               | Baseline | Fusion  | Improvement
  ---------------------|----------|---------|------------
  Variance mean        |    109.4 |    77.6 | -29% noise
  Variance std         |    154.1 |   105.4 | -32% stability
  Confidence           |    0.643 |   0.686 | +7%
  Keypoint spread std  |      4.5 |     1.3 | -72% jitter
  Presence ratio       |   93.4%  |  94.6%  | +1.3pp

Person count still fluctuates near threshold — tracked as known issue.

Verified on real hardware: COM6 (node 1) + COM9 (node 2) on ruv.net.

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

* fix(ui): add client-side lerp smoothing to pose renderer

Keypoints now interpolate between frames (alpha=0.25) instead of
jumping directly to new positions. This eliminates visual jitter
that persists even with server-side EMA smoothing, because the
renderer was drawing every WebSocket frame at full rate.

Applied to skeleton, keypoints, and dense body rendering paths.

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

* feat: DynamicMinCut person separation + UI lerp smoothing

- Added ruvector-mincut dependency to sensing server
- Replaced variance-based person scoring with actual graph min-cut on
  subcarrier temporal correlation matrix (Pearson correlation edges,
  DynamicMinCut exact max-flow)
- Recalibrated feature scaling for real ESP32 data ranges
- UI: client-side lerp interpolation (alpha=0.25) on keypoint positions
- Dampened procedural animation (noise, stride, extremity jitter)
- Person count thresholds retuned for mincut ratio

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

* docs: update CHANGELOG with v0.5.1-v0.5.3 releases

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

v0.5.2-esp32

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fix(server): correct RSSI byte offset in frame parser (#332)

The server parsed rssi from buf[14] and noise_floor from buf[15], but
the firmware (csi_collector.c) packs them at buf[16] and buf[17]:

  Firmware:  n_subcarriers=u16(6-7) freq=u32(8-11) seq=u32(12-15) rssi=i8(16)
  Server:    n_subcarriers=u8(6)    freq=u16(8-9)  seq=u32(10-13) rssi=i8(14) ← WRONG

This caused RSSI to read the high byte of the sequence counter instead
of the actual signed RSSI value, producing positive values (e.g., +9)
instead of the correct negative values (e.g., -46 dBm).

Added inline documentation of the frame layout matching csi_collector.c.

Closes #332

v0.5.1-esp32

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fix(firmware,server): watchdog crash + no detection from edge vitals (#…

…321, #323)

* fix(firmware,server): watchdog crash on busy LANs + no detection from edge vitals (#321, #323)

**Firmware (#321):** edge_dsp task now batch-limits frame processing to 4
frames before a 10ms yield. On corporate LANs with high CSI frame rates,
the previous 1-tick-per-frame yield wasn't enough to prevent IDLE1
starvation and task watchdog triggers.

**Sensing server (#323):** When ESP32 runs the edge DSP pipeline (Tier 2+),
it sends vitals packets (magic 0xC5110002) instead of raw CSI frames.
Previously, the server broadcast these as raw edge_vitals but never
generated a sensing_update, so the UI showed "connected" but "0 persons".
Now synthesizes a full sensing_update from vitals data including
classification, person count, and pose generation.

Closes #321
Closes #323

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

* fix(firmware): address review findings — idle busy-spin and observability

- Fix pdMS_TO_TICKS(5)==0 at 100Hz causing busy-spin in idle path (use
  vTaskDelay(1) instead)
- Post-batch yield now 2 ticks (20ms) for genuinely longer pause
- Add s_ring_drops counter to ring_push for diagnosing frame drops
- Expose drop count in periodic vitals log line

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

* fix(server): set breathing_band_power for skeleton animation from vitals

When presence is detected via edge vitals, set breathing_band_power to
0.5 so the UI's torso breathing animation works. Previously hardcoded
to 0.0 which made the skeleton appear static even when breathing rate
was being reported.

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

v0.5.0-esp32

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feat: ADR-063/064 mmWave sensor fusion + multimodal ambient intellige…

…nce (#269)

* docs: ADR-063 mmWave sensor fusion with WiFi CSI

60 GHz mmWave radar (Seeed MR60BHA2, HLK-LD2410/LD2450) fusion
with WiFi CSI for dual-confirm fall detection, clinical-grade
vitals, and self-calibrating CSI pipeline.

Covers auto-detection, 6 supported sensors, Kalman fusion,
extended 48-byte vitals packet, RuVector/RuvSense integration
points, and 6-phase implementation plan.

Based on live hardware capture from ESP32-C6 + MR60BHA2 on COM4.

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

* feat(firmware): ADR-063 mmWave sensor fusion — full implementation

Phase 1-2 of ADR-063:

mmwave_sensor.c/h:
- MR60BHA2 UART parser (60 GHz: HR, BR, presence, distance)
- LD2410 UART parser (24 GHz: presence, distance)
- Auto-detection: probes UART for known frame headers at boot
- Mock generator for QEMU testing (synthetic HR 72±2, BR 16±1)
- Capability flag registration per sensor type

edge_processing.c/h:
- 48-byte fused vitals packet (magic 0xC5110004)
- Kalman-style fusion: mmWave 80% + CSI 20% when both available
- Automatic fallback to CSI-only 32-byte packet when no mmWave
- Dual presence flag (Bit3 = mmwave_present)

main.c:
- mmwave_sensor_init() called at boot with auto-detect
- Status logged in startup banner

Fuzz stubs updated for mmwave_sensor API.
Build verified: QEMU mock build passes.

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

* fix(firmware): correct MR60BHA2 + LD2410 UART protocols (ADR-063)

MR60BHA2: SOF=0x01 (not 0x5359), XOR+NOT checksums on header and
data, frame types 0x0A14 (BR), 0x0A15 (HR), 0x0A16 (distance),
0x0F09 (presence). Based on Seeed Arduino library research.

LD2410: 256000 baud (not 115200), 0xAA report head marker,
target state byte at offset 2 (after data_type + head_marker).

Auto-detect: probes MR60 at 115200 first, then LD2410 at 256000.
Sets final baud rate after detection.

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

* feat: ADR-063 Phase 6 server-side mmWave + CSI fusion bridge

Python script reads both serial ports simultaneously:
- COM4 (ESP32-C6 + MR60BHA2): parses ESPHome debug output for HR, BR, presence, distance
- COM7 (ESP32-S3): reads CSI edge processing frames

Kalman-style fusion: mmWave 80% + CSI 20% for vitals, OR gate for presence.

Verified on real hardware: mmWave HR=75bpm, BR=25/min at 52cm range,
CSI frames flowing concurrently. Both sensors live for 30 seconds.

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

* docs: ADR-064 multimodal ambient intelligence roadmap

25+ applications across 4 tiers from practical to exotic:
- Tier 1 (build now): zero-FP fall detection, sleep monitoring,
  occupancy HVAC, baby breathing, bathroom safety
- Tier 2 (research): gait analysis, stress detection, gesture
  control, respiratory screening, multi-room activity
- Tier 3 (frontier): cardiac arrhythmia, RF tomography, sign
  language, cognitive load, swarm sensing
- Tier 4 (exotic): emotion contagion, lucid dreaming, plant
  monitoring, pet behavior

Priority matrix with effort estimates. All P0-P1 items work with
existing hardware (ESP32-S3 + MR60BHA2 + BH1750).

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

* fix(ci): add ESP_ERR_NOT_FOUND to fuzz stubs

mmwave_sensor stub returns ESP_ERR_NOT_FOUND which wasn't
defined in the minimal esp_stubs.h for host-based fuzz testing.

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