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docs(adr-187): mark P1-P3 done, verify acceptance criteria

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Verified all 6 acceptance criteria against current file contents and checked them.
Set Status to Accepted; marked P1/P2/P3 DONE (1fb5397dd); left P4 as ACCEPTED-FUTURE (#645).

To make criterion 4 genuinely true (live ESP32 17-keypoint feature nowhere advertised
without the first-cut/below-target/runtime-stub caveat), added the caveat to the three
remaining live-pose advertisements in README.md: the recommended-hardware capability
table, the hero image caption, and the Live-ESP32-pipeline note.

Refs #509, #1125
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2026-07-21 16:13:09 -07:00
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README.md
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@@ -128,7 +128,7 @@ pip install "ruview[client]" # or: pip install "wifi-densepose[clie
>
> | Option | Hardware | Cost | Full CSI | Capabilities |
> |--------|----------|------|----------|-------------|
> | **ESP32 + Cognitum Seed** (recommended) | ESP32-S3 + [Cognitum Seed](https://cognitum.one) | ~$140 | Yes | Presence, motion, breathing, heart rate, fall detection, multi-person counting, 17-keypoint pose (signed Cog binary), 105-cog catalog, persistent vector store, kNN search, witness chain, MCP proxy |
> | **ESP32 + Cognitum Seed** (recommended) | ESP32-S3 + [Cognitum Seed](https://cognitum.one) | ~$140 | Yes | Presence, motion, breathing, heart rate, fall detection, multi-person counting, 17-keypoint pose (signed Cog binary — first-cut on-device model, see [Model weights: what's real, what's not](#model-weights-whats-real-whats-not)), 105-cog catalog, persistent vector store, kNN search, witness chain, MCP proxy |
> | **ESP32 Mesh** | 3-6× ESP32-S3 + WiFi router | ~$54 | Yes | Same capabilities as above without the persistent-memory features |
> | **ESP32-C6 research node** ([ADR-110](docs/adr/ADR-110-esp32-c6-firmware-extension.md), [witness](docs/WITNESS-LOG-110.md), [reviewer guide](docs/ADR-110-REVIEW-GUIDE.md), [firmware v0.7.0](https://github.com/ruvnet/RuView/releases/tag/v0.7.0-esp32)) | ESP32-C6-DevKit ($6–10) | ~$10 | Yes (Wi-Fi 6 capable) | Same CSI pipeline as S3 with the dual-target firmware. **Firmware-side ADR-110 substrate now closed** (v0.7.0): ESP-NOW cross-board mesh quantified at **99.56 % match / 104 µs smoothed offset stdev / 3.95× EMA suppression** over a 5-min two-board soak (witness §A0.10), 32-byte UDP sync packet with operator-tunable cadence (§A0.12), ADR-018 byte 19 bit 4 wire-fix sourced from the working ESP-NOW path (§A0.13). Wire format ready for HE-LTF PPDU tagging in ADR-018 bytes 18-19 (firmware encoder + Rust + Python decoders verified end-to-end across 23 unit tests). LP-core motion-gate RISC-V program and Wi-Fi 6 soft-AP with TWT Responder both ship as opt-in code paths (default off). **Hardware-gated for measurement**: HE-LTF live subcarrier capture needs an 11ax AP (IDF v5.4 doesn't expose AP-side HE config — §A0.6); ~5 µA LP-core hibernation needs an INA meter to capture; 802.15.4 raw RX is broken in IDF v5.4 (workaround: ESP-NOW transport, shipped + measured). See witness log for the empirical / claimed split. |
> | **Research NIC** | Intel 5300 / Atheros AR9580 | ~$50-100 | Yes | Full CSI with 3x3 MIMO |
@@ -145,7 +145,7 @@ pip install "ruview[client]" # or: pip install "wifi-densepose[clie
<img src="assets/v2-screen.png" alt="WiFi DensePose — Live pose detection with setup guide" width="800">
</a>
<br>
<em>Real-time pose skeleton from WiFi CSI signals — no cameras, no wearables</em>
<em>Real-time pose skeleton from WiFi CSI signals — no cameras, no wearables (demo visualization; the live CSI-only single-ESP32 17-keypoint model is still first-cut — see <a href="#model-weights-whats-real-whats-not">Model weights: what's real, what's not</a>)</em>
<br><br>
<a href="https://ruvnet.github.io/RuView/"><strong>▶ Live Observatory Demo</strong></a>
&nbsp;|&nbsp;
@@ -157,7 +157,7 @@ pip install "ruview[client]" # or: pip install "wifi-densepose[clie
> The [server](#-quick-start) is optional for visualization and aggregation — the ESP32 [runs independently](#esp32-s3-hardware-pipeline) for presence detection, vital signs, and fall alerts.
>
> **Live ESP32 pipeline**: Connect an ESP32-S3 node → run the [sensing server](#sensing-server) → open the [pose fusion demo](https://ruvnet.github.io/RuView/pose-fusion.html) for real-time dual-modal pose estimation (webcam + WiFi CSI). See [ADR-059](docs/adr/ADR-059-live-esp32-csi-pipeline.md).
> **Live ESP32 pipeline**: Connect an ESP32-S3 node → run the [sensing server](#sensing-server) → open the [pose fusion demo](https://ruvnet.github.io/RuView/pose-fusion.html) for real-time dual-modal pose estimation (webcam + WiFi CSI). See [ADR-059](docs/adr/ADR-059-live-esp32-csi-pipeline.md). (The webcam supplies ground-truth pose in this dual-modal demo; the CSI-only on-device 17-keypoint model is still first-cut — see [Model weights: what's real, what's not](#model-weights-whats-real-whats-not).)
>
> **three.js scene gallery** at [`/three.js/`](https://ruvnet.github.io/RuView/three.js/) — five progressively richer ADR-097 demos: helpers, cinematic, GLTF skinned, FBX skinned, and a live MediaPipe→Mixamo retargeting feed driven by ESP32 CSI. Demos 04 and 05 require a local Mixamo `X Bot.fbx` (license boundary — not redistributed).