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+# ADR-180: Through-Wall Camera↔CSI Hand-off Demo ("Behind the Wall")
+
+| Field | Value |
+|-------|-------|
+| **Status** | Proposed |
+| **Date** | 2026-06-15 |
+| **Deciders** | ruv |
+| **Codename** | **BEHIND-THE-WALL** |
+| **Builds on** | ADR-079 (camera ground-truth training), ADR-031 (sensing-first RF mode), ADR-134 (CSI→CIR multipath), ADR-029/030 (RuvSense multistatic + persistent field), ADR-024 (AETHER re-ID), ADR-151 (per-room calibration), ADR-173 (metric-locked PCK), ADR-095/096 (rvcsi nexmon) |
+
+## Context
+
+### The demo we want
+A single self-contained **HTML page** that tells one honest, visceral story:
+
+1. You stand in front of the laptop. The camera tracks your **full skeletal pose**;
+   the WiFi-CSI model, trained on *your* movements moments earlier, infers the **same
+   skeleton** in parallel — a side-by-side "camera vs RF agree" view.
+2. You **walk out the door and behind the wall**. The camera **goes blind** (you are
+   occluded — it honestly shows "no person in frame"). The CSI model **keeps inferring
+   your skeleton** from the WiFi signal alone — the 3D figure keeps walking, behind the
+   wall, smoothly. A badge flips from `CAMERA` to `RF-INFERRED (through-wall)`.
+3. You **walk back into view**. The camera **re-acquires**; the badge flips back to
+   `CAMERA`, and the RF-inferred and camera skeletons reconverge.
+
+This is the "WiFi sees through walls" demo — and the user explicitly wants the **inferred
+skeleton through the wall**, not just a blob. The project's "prove everything / no AI-slop"
+bar means we make that claim **only because we measure it**: a second camera on the far side
+of the wall records ground-truth pose *behind* the wall, so the through-wall skeleton's
+accuracy is a **reported, reproducible number** — never an unfalsifiable "trust me."
+
+### Honest capability framing (the load-bearing section)
+Through-wall **per-joint skeletal inference from WiFi CSI is not a generally-validated
+capability** in open settings — WiFi-DensePose (CMU) is camera-*co-located*. What makes it
+defensible *here* is the tightly-controlled regime and the measurement:
+
+- **Controlled regime:** one room, one subject (you), one doorway, a model **camera-supervised
+  on your exact gait and your exact through-door transition** (ADR-079) minutes earlier. This
+  is in-distribution for *this* demo, not a universal claim.
+- **Measured, not asserted:** a far-side camera (cognitum-v0 has 17 `/dev/video*` nodes — use
+  one, or a phone) records ground-truth pose behind the wall. The through-wall CSI skeleton is
+  scored against it with the metric-locked PCK harness (ADR-173). **We publish the number.**
+- **Uncertainty is rendered, not hidden:** the through-wall skeleton is drawn **translucent**,
+  with a live **per-joint confidence** and an explicit `RF-INFERRED` badge. High-confidence
+  joints render solid; low-confidence joints fade. It never masquerades as the camera's
+  ground-truth pose.
+
+| While… | Camera | WiFi CSI (S3 / Pi5 nexmon, fused) | 60 GHz mmWave (C6 + MR60BHA2) |
+|--------|--------|-----------------------------------|-------------------------------|
+| In frame | **Full 17-kpt pose** — ground truth | full skeleton (supervised model) — *agrees with camera* | presence + range + micro-motion |
+| Behind a **drywall** | nothing (occluded) | **inferred full skeleton** (camera-supervised model + multistatic fusion), confidence-scored, **measured vs far-side camera** | presence + range + breathing — independent through-thin-wall confirm |
+| Behind **brick/metal** | nothing | degrades to coarse motion/position only — report honestly | blocked |
+
+**The claim — stated precisely:** *"A WiFi-CSI model, camera-supervised on this subject and
+room, infers a continuous skeletal pose that tracks the subject through a drywall partition;
+through-wall accuracy is measured at X% PCK@k against a far-side camera (declared, not
+claimed)."* If X turns out low, that is the **honest result we report** — the skeleton is still
+rendered (the user wants it) but flagged with its true confidence, and the headline number is
+whatever we measured, good or bad.
+
+### Why multistatic + supervision is the enabler
+A single node behind a wall sees only "something moved." Three spatially-diverse vantage points
+around the doorway (RuvSense multistatic + cross-viewpoint fusion, ADR-029/030) triangulate the
+moving scatterer — drywall attenuates and diffracts 2.4/5 GHz but does not block it — giving the
+model a rich enough multipath signature to regress a skeleton it was *trained* to associate with
+your through-door motion. AETHER re-ID embeddings (ADR-024) keep it locked to **you** across the
+camera→RF→camera hand-off.
+
+### Available hardware (the user's actual rig)
+| Role | Device | Where | Stream |
+|------|--------|-------|--------|
+| Near ground truth (visible) | Laptop / USB camera | front of workstation (ruvzen) | MediaPipe pose → keypoints |
+| **Far ground truth (validation)** | cognitum-v0 camera (1 of 17 `/dev/video*`) or a phone | **behind the wall** | MediaPipe pose → keypoints (for MEASURING the through-wall skeleton) |
+| CSI node A | ESP32-S3 (8 MB) | COM9 (ruvzen) | UDP CSI :5005 |
+| CSI + mmWave node B | ESP32-C6 + Seeed MR60BHA2 | COM12 (ruvzen) | WiFi CSI + 60 GHz FMCW presence/range |
+| CSI node C (through-wall vantage) | Pi 5, BCM43455c0 | cognitum-v0 (other room) | nexmon_csi `.pcap` → rvcsi → CsiFrame |
+| Fusion + serving | sensing-server | ruvzen :3000/:8765 | `/ws/sensing`, `/ws/pose`, new `/ws/handoff` |
+
+Place **node C (Pi 5) and the far camera on the far side of the wall** — the Pi 5 gives the
+fuser a vantage the camera lacks, and the far camera turns the through-wall claim into a
+measurement.
+
+## Decision
+
+Build a **camera↔CSI hand-off demo** as a thin, additive layer over existing components (no new
+heavy crate). Five parts: a multi-source capture plane, a camera-supervised calibration walk
+that **learns to infer the skeleton through the wall**, a **hand-off state machine**, a
+**dead-reckoning smoother** so dropped CSI never makes the figure jump, and a single-file HTML
+viewer that renders the inferred skeleton with honest confidence.
+
+### 1. Capture plane (reuse, don't rebuild)
+- **Near camera:** `scripts/collect-ground-truth.py` already does MediaPipe pose + ESP32 CSI
+  paired capture (ADR-079). Extend it to also subscribe to the Pi 5 nexmon stream (rvcsi), the
+  C6 mmWave presence, **and the far camera**, so every frame is
+  `(near_pose|null, far_pose|null, csi_S3, csi_C6, mmwave_C6, csi_Pi5, t)`.
+- **CSI nodes:** S3 over UDP :5005, Pi 5 via `rvcsi` (vendor/rvcsi nexmon adapter → `CsiFrame`),
+  C6 WiFi CSI + the MR60BHA2 60 GHz presence/range/breathing.
+- **Fusion:** all CSI sources into the existing `MultistaticFuser`
+  (`signal/src/ruvsense/multistatic.rs`); node positions around the doorway via
+  `--node-positions` (geometric-diversity index drives confidence). **#1049:** with 3
+  independently-clocked nodes set `WDP_GUARD_INTERVAL_US` to the real inter-node spread or
+  fusion demotes.
+
+### 2. Calibration walk — "it learns my movements **and infers them through the wall**" (ADR-079)
+A 3–5 minute guided routine. The HTML page scripts the walk: stand, step left/right, walk to the
+door, **cross fully behind the wall and back**, repeat — covering the visible AND the occluded
+zone, because **both cameras label ground truth**:
+- **Visible-zone supervision:** near camera labels pose; synchronized CSI window is the input.
+- **Through-wall supervision (the key part):** while you are behind the wall, the **far camera**
+  labels your pose. So the CSI→skeleton model is trained on *real behind-wall poses* paired with
+  the *behind-wall multistatic CSI* — the model genuinely learns to infer your skeleton through
+  the wall, supervised by ground truth, not extrapolated blindly.
+- Train/fine-tune on `ruvultra` (RTX 5080) if available, else the local recipe. Persist as a
+  per-room calibration bank (ADR-151 `baseline → enroll → extract → train`). AETHER re-ID
+  embeddings (ADR-024) bind the track to you across the hand-off.
+- **Held-out split:** reserve some behind-wall passes for evaluation so through-wall PCK is
+  measured on data the model never trained on (no leakage — the ADR-152 measurement discipline).
+
+### 3. Hand-off state machine (`sensing-server/src/handoff.rs`, < 300 lines)
+States: `CAMERA` → `HANDOFF_OUT` → `RF_INFERRED` → `HANDOFF_IN` → `CAMERA` (+ `LOST`).
+- **`CAMERA`** — near camera has a confident pose → render it; RF-inferred skeleton ghosted
+  alongside for the "they agree" effect.
+- **`HANDOFF_OUT`** — near-camera confidence drops at the doorway **while** CSI motion stays high
+  and the multistatic track heads into the door zone → cross-fade source camera→RF.
+- **`RF_INFERRED`** — no camera pose; the CSI model emits a **full 17-kpt skeleton** + per-joint
+  confidence; AETHER confirms it is still you. Render the translucent skeleton + confidence,
+  badge `RF-INFERRED (through-wall)`. (When fusion confidence is too low for a credible skeleton,
+  degrade gracefully to a coarse marker rather than a flailing one — honest fallback.)
+- **`HANDOFF_IN`** — near camera re-acquires a pose positionally consistent with the last RF
+  skeleton (continuity gate) → cross-fade RF→camera.
+- **`LOST`** — neither source for N cycles → "no track," never invented.
+
+Fail-closed: `RF_INFERRED` requires real multistatic motion energy + an AETHER identity match
+above calibrated floors; absent that → `LOST`, never a phantom. Mirrors the governed-trust gate
+(ADR-031 / ADR-141).
+
+### 4. Dead reckoning & smoothing — fluid, never jumpy (the user's requirement)
+CSI does **not** arrive cleanly: UDP frames drop, nexmon `.pcap` has gaps, the fuser skips
+cycles when the #1049 guard rejects a spread, and the model's per-frame skeleton jitters. Render
+only on real frames and the figure teleports and shakes — which also *reads as fake*. A
+**predict/correct (dead-reckoning) layer** keeps the skeleton continuous and smooth between
+measurements, with **bounded** extrapolation so we never invent motion that didn't happen:
+
+- **Per-joint constant-velocity Kalman filter** — reuse `signal/src/ruvsense/pose_tracker.rs`
+  (the project's existing 17-keypoint Kalman tracker with AETHER re-ID). The renderer runs at a
+  **fixed ~30 Hz, decoupled from CSI arrival**:
+  - **Measurement this tick** → Kalman *update* (correct) each joint with the new inferred pose.
+  - **Dropped CSI this tick** → Kalman *predict* only: advance each joint by `x += v·dt`, so the
+    skeleton keeps moving along its trajectory instead of freezing then snapping. **This is the
+    dead reckoning** — the limbs keep their motion through a dropout.
+- **Confidence decay (honesty governor):** every predict-only tick multiplies confidence and
+  widens covariance. Dead reckoning is trusted for a **bounded** horizon (default ≤ ~500 ms,
+  `WDP_DEADRECKON_MAX_MS`); past it, confidence hits the floor → state machine → `LOST`. **We
+  coast briefly to stay smooth; we never coast forever to fake a track.** Someone who actually
+  stopped behind the wall converges to a still pose then `LOST`, not perpetual phantom walking.
+- **Re-acquire smoothing:** a returning measurement after a gap is blended in with a
+  critically-damped step (no overshoot) over 2–3 ticks, so the skeleton eases onto truth.
+- **Client render smoothing (already present):** `ui/observatory/js/figure-pool.js`
+  `applyKeypoints` already `lerp`s joints with a small velocity overshoot for secondary motion;
+  the hand-off viewer reuses it. The camera↔RF cross-fade is an alpha-lerp over ~300 ms.
+
+**Dead-reckoning honesty invariants (testable):**
+1. Predicted-only frames carry `"dead_reckoned": true` + `"age_ms"`; the UI dims them —
+   extrapolation is never shown as a fresh measurement.
+2. Confidence is **monotonically non-increasing** across consecutive predict-only ticks.
+3. After `WDP_DEADRECKON_MAX_MS` of silence the state **must** become `LOST` (pinned test:
+   measurements then silence → assert transition within the horizon; no perpetual motion).
+4. Dead reckoning extrapolates an **existing** track only — no measurement ever ⇒ no track ⇒
+   `LOST`, never a phantom from zero.
+
+### 5. The HTML demo (single file, vanilla — mirrors the Observatory)
+`ui/through-wall/index.html` (+ a small JS bundle, zero build step, like `ui/observatory/`):
+- **Left:** near camera feed with the MediaPipe skeleton overlaid while visible; greys to
+  "CAMERA BLIND" when occluded. (Optional second tile: the far camera, shown only in a
+  "validation" view, not the hero view.)
+- **Right:** a top-down 3D room (Three.js) with the **wall** drawn, the doorway, the three
+  sensor positions, and the figure: a **solid skeleton** in `CAMERA`, a **translucent skeleton
+  with per-joint confidence fade** in `RF_INFERRED`, eased by the dead-reckoning smoother.
+- **Banner / `BannerState`** (strict, mirrors rufield-viewer): `CAMERA` / `RF-INFERRED — through
+  wall (conf X%, measured Y% PCK@k)` / `DEAD-RECKONED (age N ms)` / `LOST` — mutually exclusive,
+  with a one-line honesty caption. The measured through-wall PCK is shown, not invented.
+- Consumes a new `GET /ws/handoff` WS/SSE topic of `HandoffFrame`s; `?demo=1` replays a recorded
+  session badged `REPLAY`.
+
+### Output contract (`HandoffFrame`, JSON)
+```jsonc
+{
+  "t_ns": 1718400000000,
+  "state": "RF_INFERRED",             // CAMERA | HANDOFF_OUT | RF_INFERRED | HANDOFF_IN | LOST
+  "source": "fused_csi",              // camera | fused_csi | mmwave | dead_reckoned
+  "pose": [[x,y,z,conf], …×17],       // inferred skeleton WITH per-joint confidence (present in CAMERA/HANDOFF/RF_INFERRED)
+  "pose_confidence": 0.58,            // aggregate; the rendered translucency
+  "identity_match": 0.81,             // AETHER re-ID — is it still you?
+  "coarse": { "cell":[x,y], "zone":"behind_wall", "heading_deg":95, "node_diversity":0.48 },
+  "dead_reckoned": false,             // true on predict-only (extrapolated) ticks
+  "age_ms": 0,                        // ms since the last real measurement (0 = fresh)
+  "camera_blind": true,
+  "measured_pck": { "k": 20, "value": null },  // filled from the far-camera validation run; null until measured
+  "caption": "RF-inferred skeleton — model camera-supervised on this room; through-wall PCK measured separately"
+}
+```
+
+## Phased plan (each phase independently demoable + falsifiable)
+- **P1 — wiring (no claim):** 3-source CSI capture (S3+C6+Pi5) + near camera into the multistatic
+  fuser. Gate: `/ws/sensing` shows ≥3 active nodes + a fused position with the camera running.
+- **P2 — supervised calibration + through-wall training:** the guided walk with **both cameras**;
+  fine-tune CSI→skeleton on visible AND far-camera-labeled behind-wall poses (ADR-079). Gate:
+  while-visible PCK declared (metric-locked, ADR-173) on a held-out segment.
+- **P3 — MEASURE the through-wall skeleton:** score the RF-inferred skeleton against the far
+  camera on held-out behind-wall passes → **publish the through-wall PCK@k** (good or bad). Gate:
+  a committed eval script reproduces the number; honest negative if low.
+- **P4 — hand-off + dead reckoning + HTML:** the camera→RF→camera transition renders end-to-end,
+  smooth through dropped CSI. Gate: a recorded live walk where the camera goes blind, the inferred
+  skeleton keeps walking fluidly behind the wall, dead-reckons through dropouts without jumps, and
+  re-acquisition is position-continuous. **This is the demo.**
+- **P5 — multi-modal corroboration (optional):** overlay C6 60 GHz presence/range as an
+  independent through-thin-wall confirm (two physics, one conclusion).
+
+## Consequences
+
+### Positive
+- A genuinely compelling demo that does what the user asked — **infers and renders the skeleton
+  through the wall** — while staying honest because the through-wall accuracy is **measured**
+  against a far-side camera, not claimed. Reuses the multistatic fuser, ADR-079 supervision, the
+  Kalman pose tracker, AETHER re-ID, the calibration crate, and the Observatory UI: the new code
+  is a hand-off module + dead-reckoning smoother + an HTML page.
+
+### Negative / Risks
+- **Through-wall skeletal accuracy may be modest or poor.** That is acceptable *iff* reported
+  honestly — the headline is the measured PCK, whatever it is; the skeleton renders with its true
+  per-joint confidence (low-confidence joints fade), never as fake certainty.
+- **Material dependence:** drywall good; brick/metal degrades to coarse-only — shoot on drywall
+  and say so.
+- **3-node clock sync** is the #1049 hazard — tune `WDP_GUARD_INTERVAL_US`.
+- **Per-room, per-subject:** the model that "learned your movements" does not transfer without
+  re-calibration — stated on the page.
+- **Over-claiming is the failure mode.** Mitigations baked in: translucent confidence-faded
+  skeleton, `dead_reckoned`/`age_ms` flags, the measured-PCK banner, bounded extrapolation→`LOST`.
+
+### Neutral
+- No new heavy crate; signal-path proof (`verify.py`) untouched — capture/fusion/UI orchestration
+  over hardened, already-reviewed components.
+
+## Acceptance criteria (falsifiable — "prove the haters wrong")
+On a recorded live session, all must hold:
+1. A contiguous window where the **near camera reports no person** (verifiable from raw frames)
+   **and** the system renders an `RF_INFERRED` skeleton.
+2. The inferred skeleton's **gross motion matches reality** — direction of travel and rough gait
+   phase — confirmed against the **far camera** (not eyeballed).
+3. **Through-wall per-joint accuracy is MEASURED** against the far camera and **reported** as
+   PCK@k from a committed script. Low is fine *if* honestly published; fabricated is not.
+4. The figure is **smooth through dropped CSI** — no teleports/jitter — and every predicted-only
+   frame is flagged `dead_reckoned`; after `WDP_DEADRECKON_MAX_MS` of silence it goes `LOST`.
+5. Re-acquisition is **position-continuous** (camera re-detects within a cell of the last RF
+   position), and AETHER confirms identity across the hand-off.
+6. Every number (visible PCK, through-wall PCK, confidences) is MEASURED and reproducible — no
+   hand-typed metrics.
+
+A demo that cannot meet (1)–(2) and (4)–(5) on the available hardware is reported as a **negative
+result** (honest), not dressed up; a poor (3) is published as the real number.
+
+## Links
+- ADR-079 — camera ground-truth training (supervision pipeline; extended here to a far camera)
+- ADR-031 — sensing-first RF mode / coherence gate (fail-closed honesty pattern)
+- ADR-134 — CSI→CIR multipath (through-wall multipath physics)
+- ADR-029 / ADR-030 — RuvSense multistatic + persistent field (the localization engine)
+- ADR-024 — AETHER contrastive re-ID (identity lock across the hand-off)
+- ADR-151 — per-room calibration crate (bank persistence)
+- ADR-152 / ADR-173 — measurement discipline + metric-locked PCK (the honest accuracy readout)
+- ADR-095 / ADR-096 — rvcsi nexmon (Pi 5 BCM43455c0 capture)
+- `signal/src/ruvsense/pose_tracker.rs` — 17-kpt Kalman tracker reused for dead reckoning
+- `ui/observatory/` — the vanilla-JS 3D viewer pattern this demo mirrors