From 73ce72d39c044c4088c246098cd660706e230ed2 Mon Sep 17 00:00:00 2001 From: ruv Date: Fri, 3 Apr 2026 08:16:23 -0400 Subject: [PATCH] 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 --- README.md | 56 +++++++++++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 54 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 5b2ea97a..f774814d 100644 --- a/README.md +++ b/README.md @@ -81,9 +81,60 @@ docker run -p 3000:3000 ruvnet/wifi-densepose:latest > --- -### What's New in v0.5.4 +### What's New in v0.5.5
+Advanced Sensing: SNN + MinCut + WiFlow + Multi-Frequency Mesh + +**v0.5.5 adds four new sensing capabilities** built on the [ruvector](https://github.com/ruvnet/ruvector) ecosystem: + +| Capability | What it does | ADR | +|-----------|-------------|-----| +| **Spiking Neural Network** | Adapts to your room in <30s with STDP online learning — no labels, no batches, 16-160x less compute | [ADR-074](docs/adr/ADR-074-spiking-neural-csi-sensing.md) | +| **MinCut Person Counting** | Stoer-Wagner min-cut on subcarrier correlation graph — **fixes #348** (was always 4, now correct) | [ADR-075](docs/adr/ADR-075-mincut-person-separation.md) | +| **CNN Spectrogram Embeddings** | Treat CSI as a 64×20 image → 128-dim embedding for environment fingerprinting (0.95+ similarity) | [ADR-076](docs/adr/ADR-076-csi-spectrogram-embeddings.md) | +| **WiFlow SOTA Architecture** | TCN + axial attention + pose decoder → 17 COCO keypoints, 1.8M params (881 KB at 4-bit) | [ADR-072](docs/adr/ADR-072-wiflow-architecture.md) | +| **Multi-Frequency Mesh** | Channel hopping across 6 bands, neighbor WiFi as passive radar illuminators | [ADR-073](docs/adr/ADR-073-multifrequency-mesh-scan.md) | + +```bash +# Live RF room scan (spectrum visualization) +node scripts/rf-scan.js --port 5006 --duration 30 + +# Correct person counting (fixes #348) +node scripts/mincut-person-counter.js --port 5006 + +# SNN real-time adaptation +node scripts/snn-csi-processor.js --port 5006 + +# CNN spectrogram embeddings +node scripts/csi-spectrogram.js --replay data/recordings/*.csi.jsonl + +# WiFlow 17-keypoint pose training +node scripts/train-wiflow.js --data data/recordings/*.csi.jsonl + +# Enable channel hopping on ESP32 +python firmware/esp32-csi-node/provision.py --port COM9 --hop-channels "1,6,11" +``` + +**Validated benchmarks:** + +| Metric | v0.5.4 | v0.5.5 | +|--------|--------|--------| +| Person counting | Broken (always 4) | **Correct** (MinCut, 24/24) | +| WiFi channels | 1 | **6** (multi-freq hopping) | +| Null subcarriers | 19% blocked | **16%** (frequency diversity) | +| Pose model | 16K params (FC only) | **1.8M params** (WiFlow) | +| Online adaptation | None | **<30s** (SNN STDP) | +| Fingerprint dims | 8 | **128** (CNN spectrogram) | +| Multi-node fusion | Average | **GATv2 attention** | +| New scripts | 0 | **15+** | +| New ADRs | 3 | **8** (069-076) | + +
+ +### What's New in v0.5.4 + +
Cognitum Seed Integration + Camera-Free Pose Training **v0.5.4 transforms RuView from a real-time sensing tool into a persistent edge AI system.** Your ESP32 now remembers what it senses, learns without cameras, and proves its data cryptographically. @@ -1117,7 +1168,8 @@ Download a pre-built binary — no build toolchain needed: | Release | What's included | Tag | |---------|-----------------|-----| -| [v0.5.4](https://github.com/ruvnet/RuView/releases/tag/v0.5.4-esp32) | **Latest** — Cognitum Seed integration ([ADR-069](docs/adr/ADR-069-cognitum-seed-csi-pipeline.md)), 8-dim feature vectors at 1 Hz, RVF vector store ingest, witness chain attestation, security hardening | `v0.5.4-esp32` | +| [v0.5.5](https://github.com/ruvnet/RuView/releases/tag/v0.5.5-esp32) | **Latest** — SNN + MinCut (fixes #348) + CNN spectrogram + WiFlow 1.8M architecture + multi-freq mesh (6 channels) + graph transformer | `v0.5.5-esp32` | +| [v0.5.4](https://github.com/ruvnet/RuView/releases/tag/v0.5.4-esp32) | Cognitum Seed integration ([ADR-069](docs/adr/ADR-069-cognitum-seed-csi-pipeline.md)), 8-dim feature vectors, RVF store, witness chain, security hardening | `v0.5.4-esp32` | | [v0.5.0](https://github.com/ruvnet/RuView/releases/tag/v0.5.0-esp32) | mmWave sensor fusion ([ADR-063](docs/adr/ADR-063-mmwave-sensor-fusion.md)), auto-detect MR60BHA2/LD2410, 48-byte fused vitals, all v0.4.3.1 fixes | `v0.5.0-esp32` | | [v0.4.3.1](https://github.com/ruvnet/RuView/releases/tag/v0.4.3.1-esp32) | Fall detection fix ([#263](https://github.com/ruvnet/RuView/issues/263)), 4MB flash ([#265](https://github.com/ruvnet/RuView/issues/265)), watchdog fix ([#266](https://github.com/ruvnet/RuView/issues/266)) | `v0.4.3.1-esp32` | | [v0.4.1](https://github.com/ruvnet/RuView/releases/tag/v0.4.1-esp32) | CSI build fix, compile guard, AMOLED display, edge intelligence ([ADR-057](docs/adr/ADR-057-firmware-csi-build-guard.md)) | `v0.4.1-esp32` |