perf(ci): drop dead uvicorn start from perf job (#917)

Since #915 the perf job gates only on test_frame_budget.py, which drives
the CSIProcessor pipeline in-process and makes no HTTP calls. The
"Start application" step (uvicorn + `sleep 10`) was therefore dead weight:
it existed only for the now-excluded api_throughput/inference_speed tests,
wasted ~10-15 s per main-push run, and dumped ~50 misleading
"router requires hardware setup" ERROR lines into every CI log for a
server no test touched. MOCK_POSE_DATA is server-only, unused here.

Removed the step and the vestigial env. The gated test is unchanged and
passes (verified locally, 3/3).

.github/workflows/ci.yml

@@ -265,23 +265,45 @@ jobs:
       run: |
         python -m pip install --upgrade pip
         pip install -r requirements.txt
-        pip install locust
+        pip install pytest   # the perf suite is pytest, not locust
 
-    - name: Start application
-      working-directory: archive/v1
-      run: |
-        uvicorn src.api.main:app --host 0.0.0.0 --port 8000 &
-        sleep 10
+    # No "Start application" step: the gated test (test_frame_budget.py) drives
+    # the CSIProcessor pipeline in-process and makes no HTTP calls, so the old
+    # uvicorn server + `sleep 10` were dead weight — they only existed for the
+    # now-excluded api_throughput/inference_speed tests, and on every run dumped
+    # ~50 misleading "router requires hardware setup" ERROR lines for a server
+    # no test touched. MOCK_POSE_DATA is server-only and unused here.
 
     - name: Run performance tests
+      working-directory: archive/v1
       run: |
-        locust -f tests/performance/locustfile.py --headless --users 50 --spawn-rate 5 --run-time 60s --host http://localhost:8000
+        # Gate only on the genuine, deterministic perf guard:
+        # test_frame_budget.py times the *real* CSIProcessor pipeline against
+        # the ADR 50 ms per-frame budget (single-frame, p95 over 100 frames,
+        # +Doppler) — a true regression signal.
+        #
+        # test_api_throughput.py / test_inference_speed.py are excluded: every
+        # test there is a TDD red-phase stub (suffix `_should_fail_initially`)
+        # that times a *mock that sleeps* — meaningless as a perf signal, with
+        # machine-dependent wall-clock asserts (e.g. `actual_rps >= 40`,
+        # `batch_time < individual_time`) that are inherently flaky on shared
+        # CI runners, plus a cross-class fixture-scope bug. Forcing them green
+        # would be manufacturing a false signal; they stay in-repo for local
+        # TDD but do not gate CI until the underlying features are implemented.
+        #
+        # `python -m pytest` (not the bare `pytest` script) puts the cwd
+        # (archive/v1) on sys.path so `from src.core...` resolves — the bare
+        # script omits cwd and raises ModuleNotFoundError: No module named 'src'.
+        # -o addopts="" drops the root pyproject's --cov/--cov-fail-under=100.
+        python -m pytest tests/performance/test_frame_budget.py \
+          -o addopts="" -v --junitxml=perf-junit.xml
 
     - name: Upload performance results
+      if: always()
       uses: actions/upload-artifact@v4
       with:
         name: performance-results
-        path: locust_report.html
+        path: archive/v1/perf-junit.xml
 
   # Docker Build and Test
   # NOTE: the canonical Docker build for the sensing-server is now
@@ -367,6 +389,8 @@ jobs:
     runs-on: ubuntu-latest
     needs: [docker-build]
     if: github.ref == 'refs/heads/main'
+    permissions:
+      contents: write   # gh-pages deploy needs write (GITHUB_TOKEN is read-only by default -> 403)
     steps:
     - name: Checkout code
       uses: actions/checkout@v4
@@ -384,6 +408,8 @@ jobs:
 
     - name: Generate OpenAPI spec
       working-directory: archive/v1
+      env:
+        MOCK_POSE_DATA: "true"   # no CSI hardware in CI
       run: |
         python -c "
         from src.api.main import app
@@ -394,6 +420,7 @@ jobs:
 
     - name: Deploy to GitHub Pages
       uses: peaceiris/actions-gh-pages@v4
+      continue-on-error: true   # openapi generation above is the real validation; deploy is best-effort (Pages may be disabled)
       with:
         github_token: ${{ secrets.GITHUB_TOKEN }}
         publish_dir: ./docs

CHANGELOG.md

@@ -8,6 +8,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ## [Unreleased]
 
 ### Fixed
+- **Person count no longer leaks up to 10 in heuristic mode — addresses #894.** `field_bridge::occupancy_or_fallback` returned the eigenvalue-based `FieldModel::estimate_occupancy` count **unbounded** (its internal ceiling is 10), while the sibling estimators on the same single-link data — the perturbation-energy fallback right below it and `score_to_person_count` — both cap at 3 ("1-3 for single ESP32"). On noisy / under-calibrated CSI the eigenvalue count inflated, producing the "10 persons reported when 1 present" symptom (seen when `--model` fails to load and the server runs on heuristics). Bounded the eigenvalue path to the shared `MAX_SINGLE_LINK_OCCUPANCY` (3) so every estimator on one link agrees; genuine higher counts come from the multistatic fusion path, not a single-link covariance estimate.
+- **MQTT multi-node deployments now create one Home-Assistant device per node — closes #898.** After the #872 MQTT wiring landed, the JSON→`VitalsSnapshot` bridge hard-coded a single `node_id` (the MQTT client id) and the publisher used a single `OwnedDiscoveryBuilder`, so every physical node collapsed into one device (`identifiers:["wifi_densepose_wifi-densepose-1"]`), contradicting the "one device per node" docs. The bridge now emits one snapshot per node in the sensing update's `nodes[]` (each with its own `node_id` + RSSI, falling back to a single aggregate snapshot for wifi/simulate sources), and the publisher derives a per-node builder (`OwnedDiscoveryBuilder::for_node`) that publishes discovery + availability lazily on first sight of each `node_id` and routes state to per-node topics — yielding N distinct HA devices with per-node availability/LWT. Unit-tested (distinct nodes → distinct `wifi_densepose_<node>` identifiers); 71 MQTT tests pass.
 - **Person count no longer pinned to 1 — addresses #803.** The aggregate occupancy reported by the sensing server was derived from `smoothed_person_score`, an EMA-smoothed *activity* score (amplitude variance / motion / spectral energy). That score saturates near a single occupant — one moving person maxes it out — so it cannot discriminate occupancy *count* and stayed clamped at 1 across S3/C6 and the Python/Docker/Rust servers. Meanwhile the count-aware per-node estimates the ESP32 paths already compute (firmware `n_persons`, and the DynamicMinCut `corr_persons`) were stashed in `NodeState::prev_person_count` and then **discarded** by the aggregator (same dead-wiring class as #872). The aggregator now takes `max(activity_count, node_max)` via a unit-tested `aggregate_person_count` helper, so a node positively estimating 2–3 occupants is surfaced instead of overwritten. The fix can only ever *raise* the count when a node reports more people, so the single-occupant case is provably never inflated (regression-guarded by test). **Second half:** the pure-CSI per-node path itself clamped its own estimate — the DynamicMinCut occupancy (`estimate_persons_from_correlation`, 0–3) was mapped to a score via `corr_persons / 3.0`, putting 2 people at 0.667, *just under* the 0.70 up-threshold of `score_to_person_count`, so the per-node count never climbed past 1 (so `node_max` was also stuck at 1 for CSI-only nodes). Replaced it with a threshold-aligned `corr_persons_to_score` mapping (1→0.40, 2→0.74, 3→0.96) whose steady state round-trips back to the same count through the EMA + hysteresis, while still gating transient noise. A convergence test replays the exact EMA loop to prove min-cut=2 now reports 2 (and documents that the old `/3.0` mapping reported 1). Full multi-person accuracy still depends on the underlying estimator quality; this removes the two server-side clamps that masked it. 586 sensing-server tests pass.
 - **MQTT publisher now actually runs (`--mqtt`) — closes #872.** The `--mqtt*` flags were defined only in `cli::Args` (dead code, referenced nowhere) while the binary parses a *separate* `main::Args` with no mqtt fields, and `main.rs` never started the `mqtt::` publisher — so MQTT/Home-Assistant integration was completely unwired (`--mqtt` errored as an unexpected argument, and even with the Docker image's `--features mqtt` build the publisher never ran). Earlier attempts chased a Docker *rebuild*; the real cause was disconnected *code*. Extracted the flags into a shared `cli::MqttArgs` (`#[command(flatten)]` into both structs), spawn the publisher on `--mqtt`, and bridge the JSON sensing broadcast into the typed `VitalsSnapshot` stream with a defensive `serde_json::Value` mapping. Verified end-to-end against `mosquitto`: 20 HA auto-discovery entities + live state (presence/person-count/…). 577 (default) / 580 (`--features mqtt`) tests pass.
 
@@ -428,7 +430,7 @@ Model release (no new firmware binary). Firmware remains at v0.6.0-esp32.
 - Security fix merged via PR #310.
 
 ### Performance
-- Presence detection: 100% accuracy on 60,630 overnight samples.
+- Presence detection: 100% accuracy on 60,630 overnight samples. *(Retracted — that recording was single-class (one sleeping person, 6,062/6,063 frames "present"), so a constant "yes" scores ~99.98%. Superseded by the honest 82.3% held-out temporal-triplet metric; see [#882](https://github.com/ruvnet/RuView/issues/882). Kept here as the in-place public record.)*
 - Inference: 0.008 ms per sample, 164K embeddings/sec.
 - Contrastive self-supervised training: 51.6% improvement over baseline.
 

archive/v1/src/services/pose_service.py

@@ -107,16 +107,25 @@ class PoseService:
     async def _initialize_models(self):
         """Initialize neural network models."""
         try:
-            # Initialize DensePose model
+            # Initialize DensePose model. DensePoseHead requires a config
+            # dict — input_channels matches the modality translator's output
+            # (256), with the standard DensePose 24 body parts and 2 (U,V)
+            # coordinates. (Previously called with no args → TypeError at
+            # startup, which broke the API service.)
+            densepose_config = {
+                'input_channels': 256,
+                'num_body_parts': 24,
+                'num_uv_coordinates': 2,
+            }
             if self.settings.pose_model_path:
-                self.densepose_model = DensePoseHead()
+                self.densepose_model = DensePoseHead(densepose_config)
                 # Load model weights if path is provided
                 # model_state = torch.load(self.settings.pose_model_path)
                 # self.densepose_model.load_state_dict(model_state)
                 self.logger.info("DensePose model loaded")
             else:
                 self.logger.warning("No pose model path provided, using default model")
-                self.densepose_model = DensePoseHead()
+                self.densepose_model = DensePoseHead(densepose_config)
             
             # Initialize modality translation
             config = {

docs/readme-details.md

@@ -122,7 +122,7 @@ node scripts/benchmark-ruvllm.js --model models/csi-ruvllm       # benchmark
 
 | What we measured | Result | Why it matters |
 |-----------------|--------|---------------|
-| **Presence detection** | **100% accuracy** | Never misses a person, never false alarms |
+| **CSI embedding quality** | **82.3% held-out temporal-triplet** | Honest label-free metric on the last 20% by time (v1's "100% presence" was a single-class recording — retracted, [#882](https://github.com/ruvnet/RuView/issues/882)) |
 | **Inference speed** | **0.008 ms** per embedding | 125,000x faster than real-time |
 | **Throughput** | **164,183 embeddings/sec** | One Mac Mini handles 1,600+ ESP32 nodes |
 | **Contrastive learning** | **51.6% improvement** | Strong pattern learning from real overnight data |
@@ -233,7 +233,7 @@ python firmware/esp32-csi-node/provision.py --port COM9 --hop-channels "1,6,11"
 | **kNN similarity search** | "Find the 10 most similar states to right now" — anomaly detection, fingerprinting | Cognitum Seed |
 | **Witness chain** | SHA-256 tamper-evident audit trail for every measurement (1,747 entries validated) | Cognitum Seed |
 | **Camera-free pose training** | 17 COCO keypoints from 10 sensor signals — PIR, RSSI triangulation, subcarrier asymmetry, vibration, BME280 | 2x ESP32 + Seed |
-| **Pre-trained model** | 82.8 KB (8 KB at 4-bit quantization), 100% presence accuracy, 0 skeleton violations | Download from release |
+| **Pre-trained model** | 82.8 KB (8 KB at 4-bit quantization), 82.3% held-out temporal-triplet accuracy (v1's "100% presence" was single-class — retracted, [#882](https://github.com/ruvnet/RuView/issues/882)) | Download from release |
 | **Sub-ms inference** | 0.012 ms latency, 171,472 embeddings/sec on M4 Pro | Any machine with Node.js |
 | **SONA adaptation** | Adapts to new rooms in <1ms without retraining | ruvllm runtime |
 | **LoRA room adapters** | Per-node fine-tuning with 2,048 parameters per adapter | Automatic |
@@ -262,7 +262,7 @@ node scripts/benchmark-ruvllm.js --model models/csi-ruvllm
 
 | What we measured | Result | Why it matters |
 |-----------------|--------|---------------|
-| **Presence detection** | **100% accuracy** | Never misses a person, never false alarms |
+| **CSI embedding quality** | **82.3% held-out temporal-triplet** | Honest label-free metric (v1's "100% presence" was single-class — retracted, [#882](https://github.com/ruvnet/RuView/issues/882)) |
 | **Person counting** | **24/24 correct** (MinCut) | Fixed the #1 user-reported issue |
 | **Inference speed** | **0.012 ms** per embedding | 83,000x faster than real-time |
 | **Throughput** | **171,472 embeddings/sec** | One Mac Mini handles 1,700+ ESP32 nodes |

docs/user-guide.md

@@ -1119,7 +1119,7 @@ What it ships (and what it does not):
 
 | Capability | Status |
 |------------|--------|
-| Presence detection (occupied / empty) | ✅ Trained head — 100% accuracy on validation |
+| Presence detection (occupied / empty) | ✅ Trained head — v2 encoder reports 82.3% held-out temporal-triplet acc (v1's "100% on validation" was a single-class recording — retracted, [#882](https://github.com/ruvnet/RuView/issues/882)) |
 | 128-dim CSI embeddings (re-ID, similarity, downstream training) | ✅ Trained encoder |
 | Single-person breathing / heart-rate | ⚠️ Server still uses heuristic DSP — model does not replace this yet |
 | 17-keypoint full-body pose | 🔬 No keypoint weights shipped yet — pose pipeline runs but without a learned head |
@@ -1824,7 +1824,7 @@ huggingface-cli download ruvnet/wifi-densepose-pretrained --local-dir models/pre
 #   model.safetensors    — 48 KB contrastive encoder
 #   model-q4.bin         — 8 KB quantized (recommended)
 #   model-q2.bin         — 4 KB ultra-compact (ESP32 edge)
-#   presence-head.json   — presence detection head (100% accuracy)
+#   presence-head.json   — presence detection head (v2 encoder: 82.3% held-out triplet acc)
 #   node-1.json          — LoRA adapter for room 1
 #   node-2.json          — LoRA adapter for room 2
 ```
@@ -1833,7 +1833,7 @@ huggingface-cli download ruvnet/wifi-densepose-pretrained --local-dir models/pre
 
 The pre-trained encoder converts 8-dim CSI feature vectors into 128-dim embeddings. These embeddings power all 17 sensing applications:
 
-- **Presence detection** — 100% accuracy, never misses, never false alarms
+- **Presence detection** — v2 encoder: 82.3% held-out temporal-triplet accuracy (v1's "100%" was a single-class recording — retracted, [#882](https://github.com/ruvnet/RuView/issues/882))
 - **Environment fingerprinting** — kNN search finds "states like this one"
 - **Anomaly detection** — embeddings that don't match known clusters = anomaly
 - **Activity classification** — different activities cluster in embedding space

firmware/esp32-csi-node/main/csi_collector.c

@@ -637,6 +637,23 @@ static void hop_timer_cb(void *arg)
     csi_hop_next_channel();
 }
 
+void csi_collector_enable_data_capture(void)
+{
+    /* MGMT-only (RuView#396) starves the CSI callback on display-less boards
+     * (RuView#521/#893): beacons alone are sparse, yield collapses to 0 pps.
+     * Without a display there is no QSPI/SPI-flash cache contention with the
+     * DATA-frame interrupt load, so capture DATA frames too. */
+    wifi_promiscuous_filter_t filt = {
+        .filter_mask = WIFI_PROMIS_FILTER_MASK_MGMT | WIFI_PROMIS_FILTER_MASK_DATA,
+    };
+    esp_err_t err = esp_wifi_set_promiscuous_filter(&filt);
+    if (err == ESP_OK) {
+        ESP_LOGI(TAG, "CSI filter upgraded to MGMT+DATA (no display, RuView#893)");
+    } else {
+        ESP_LOGW(TAG, "Failed to enable DATA-frame CSI capture: %s", esp_err_to_name(err));
+    }
+}
+
 void csi_collector_start_hop_timer(void)
 {
     if (s_hop_count <= 1) {

firmware/esp32-csi-node/main/csi_collector.h

@@ -90,6 +90,19 @@ void csi_hop_next_channel(void);
  */
 void csi_collector_start_hop_timer(void);
 
+/**
+ * Upgrade the promiscuous filter to capture DATA frames in addition to MGMT
+ * (RuView#893/#521).
+ *
+ * Called on display-less boards: the MGMT-only filter (the #396 display-crash
+ * workaround set in csi_collector_init) only fires the CSI callback on sparse
+ * management frames, so yield collapses to 0 pps under real traffic and the
+ * node looks dead. A board with no AMOLED panel has no QSPI/SPI-flash cache
+ * contention, so it can safely capture DATA frames — restoring abundant CSI.
+ * Display boards keep MGMT-only to avoid the #396 crash.
+ */
+void csi_collector_enable_data_capture(void);
+
 /**
  * Inject an NDP (Null Data Packet) frame for sensing.
  *

firmware/esp32-csi-node/main/display_task.c

@@ -9,6 +9,14 @@
 #include "display_task.h"
 #include "sdkconfig.h"
 
+/* Set true once an AMOLED panel is detected and the display task starts.
+ * Defined outside the CONFIG_DISPLAY_ENABLE guard so display_is_active()
+ * exists on headless builds too (where it stays false → CSI captures DATA
+ * frames; see RuView#893). */
+static bool s_display_active = false;
+
+bool display_is_active(void) { return s_display_active; }
+
 #if CONFIG_DISPLAY_ENABLE
 
 #include <string.h>
@@ -162,6 +170,7 @@ esp_err_t display_task_start(void)
 
     ESP_LOGI(TAG, "Display task started (Core %d, priority %d, %d fps)",
              DISP_TASK_CORE, DISP_TASK_PRIORITY, DISP_FPS_LIMIT);
+    s_display_active = true;
     return ESP_OK;
 }
 

firmware/esp32-csi-node/main/display_task.h

@@ -7,6 +7,7 @@
 #define DISPLAY_TASK_H
 
 #include "esp_err.h"
+#include <stdbool.h>
 
 #ifdef __cplusplus
 extern "C" {
@@ -22,6 +23,15 @@ extern "C" {
  */
 esp_err_t display_task_start(void);
 
+/**
+ * @return true once an AMOLED panel has been detected and the display task
+ * is running; false on headless boards (no panel, or built without display
+ * support). Used to choose the CSI promiscuous filter (RuView#893): a board
+ * with no display has no QSPI/SPI-flash contention, so it can safely capture
+ * DATA frames for proper CSI yield instead of starving on MGMT-only.
+ */
+bool display_is_active(void);
+
 #ifdef __cplusplus
 }
 #endif

firmware/esp32-csi-node/main/main.c

@@ -410,6 +410,21 @@ void app_main(void)
     }
 #endif
 
+    /* RuView#893/#521: the MGMT-only promiscuous filter (set in
+     * csi_collector_init as the #396 display-crash workaround) starves the CSI
+     * callback on display-less boards — yield collapses to 0 pps and the node
+     * looks dead despite being on the network. Now that the display probe has
+     * run, boards with no AMOLED panel (no QSPI/SPI-flash cache contention)
+     * upgrade the filter to capture DATA frames too, restoring CSI yield. */
+#ifdef CONFIG_DISPLAY_ENABLE
+    bool has_display = display_is_active();   /* runtime panel probe result */
+#else
+    bool has_display = false;                 /* display support not compiled in */
+#endif
+    if (!has_display) {
+        csi_collector_enable_data_capture();
+    }
+
     ESP_LOGI(TAG, "CSI streaming active → %s:%d (edge_tier=%u, OTA=%s, WASM=%s, mmWave=%s, swarm=%s, adapt=%s)",
              g_nvs_config.target_ip, g_nvs_config.target_port,
              g_nvs_config.edge_tier,

firmware/esp32-csi-node/release_bins/c6-adr110/SHA256SUMS.txt

@@ -1,4 +1,4 @@
-889715e9d698ad78f9978ad8b93b6af24a726b0494247201c8f0d920d9fc80ca *firmware/esp32-csi-node/release_bins/c6-adr110/bootloader.bin
-d8539e47c6f10a3344679118619e3fe01cfd66eb560ea8883268ca7c9a12efa4 *firmware/esp32-csi-node/release_bins/c6-adr110/esp32-csi-node.bin
+b0fb1f217a39c80bc95b5eb8208a0b8572ae64efa0f6d580b76caff4affe0f4d *firmware/esp32-csi-node/release_bins/c6-adr110/bootloader.bin
+4764c5b20a353895f70122816adc98f861ec20e9a8ea9b344dc0648b6341073c *firmware/esp32-csi-node/release_bins/c6-adr110/esp32-csi-node.bin
 7d2c7ac4888bfd75cd5f56e8d61f69595121183afc81556c876732fd3782c62f *firmware/esp32-csi-node/release_bins/c6-adr110/ota_data_initial.bin
 4c2cc4ffd52641e23b779bd57b3908014083ac3c1aab395756478c89e70d81f0 *firmware/esp32-csi-node/release_bins/c6-adr110/partition-table.bin

firmware/esp32-csi-node/release_bins/s3-adr110/SHA256SUMS.txt

@@ -1,3 +1,3 @@
-3c4905dd202ccabf4230cbabcc9320f250a60b1a7254eff7424780201bcb2072 *firmware/esp32-csi-node/release_bins/s3-adr110/bootloader.bin
-7a8bf9582c9031fed32f1ada44f5c41dd99bd07fadff8e5c86e07aa0f343e847 *firmware/esp32-csi-node/release_bins/s3-adr110/esp32-csi-node.bin
+b973d7eda65affb746adcfa63ceb18f779f206d240b76f01b8c9ae7485455660 *firmware/esp32-csi-node/release_bins/s3-adr110/bootloader.bin
+e21ef94aba779d534dc048c1b9da731c81e5dbe09d0645cfd70a05ad3642d3e9 *firmware/esp32-csi-node/release_bins/s3-adr110/esp32-csi-node.bin
 67222c257c0477501fd4002275638dc4262b34eb68235b8289fb1337054d322b *firmware/esp32-csi-node/release_bins/s3-adr110/partition-table.bin

firmware/esp32-csi-node/release_bins/version.txt

@@ -1,3 +1,4 @@
-0.6.6
-git-sha: cbcb389cb (pre-commit)
-built: 2026-05-21
+0.6.7
+git-sha: 8703ade9b
+built: 2026-06-02
+note: RuView#893 — display-less boards capture DATA frames (CSI yield 0pps fix); hardware-verified on ESP32-C6 (0->27 pps)

requirements.txt

@@ -36,3 +36,4 @@ scikit-learn>=1.2.0
 
 # Monitoring dependencies
 prometheus-client>=0.16.0
+psutil>=5.9.0  # system metrics — imported by health.py / metrics.py / status.py / monitoring.py

v2/crates/wifi-densepose-sensing-server/src/field_bridge.rs

@@ -21,6 +21,15 @@ const ENERGY_THRESH_2: f64 = 12.0;
 /// Perturbation energy threshold for detecting a third person.
 const ENERGY_THRESH_3: f64 = 25.0;
 
+/// Maximum occupancy a single ESP32 link can plausibly resolve (#894).
+/// The score heuristic (`score_to_person_count`) and the perturbation-energy
+/// fallback below both cap here; the eigenvalue path is bounded to match,
+/// rather than leaking its internal `min(10)` ceiling on noisy / under-
+/// calibrated CSI (the "10 persons reported when 1 present" symptom).
+/// Resolving more than this from one link's subcarrier covariance is not
+/// reliable — genuine higher counts come from the multistatic fusion path.
+const MAX_SINGLE_LINK_OCCUPANCY: usize = 3;
+
 /// Create a FieldModelConfig for single-link mode (one ESP32 node = one link).
 /// This avoids the DimensionMismatch error when feeding single-frame observations.
 pub fn single_link_config() -> FieldModelConfig {
@@ -55,9 +64,15 @@ pub fn occupancy_or_fallback(
                 return score_to_person_count(smoothed_score, prev_count);
             }
 
-            // Try eigenvalue-based occupancy first (best accuracy).
+            // Try eigenvalue-based occupancy first (best accuracy). Bound it to
+            // the same single-link maximum the sibling estimators use — the
+            // perturbation fallback below and score_to_person_count both cap at
+            // MAX_SINGLE_LINK_OCCUPANCY. Without this, estimate_occupancy's
+            // internal min(10) ceiling leaks up to 10 persons on noisy / under-
+            // calibrated CSI (#894), while every other path on the same data
+            // would report ≤3.
             if let Ok(count) = field.estimate_occupancy(&frames) {
-                return count;
+                return count.min(MAX_SINGLE_LINK_OCCUPANCY);
             } // else fall through to perturbation energy
 
             // Fallback: perturbation energy thresholds.

v2/crates/wifi-densepose-sensing-server/src/main.rs

@@ -6213,24 +6213,44 @@ async fn main() {
                                 Some(_) => 1.0,
                                 None => 0.0,
                             };
-                            let snap = mqtt::state::VitalsSnapshot {
-                                node_id: node_id.clone(),
-                                timestamp_ms: (v["timestamp"].as_f64().unwrap_or(0.0) * 1000.0) as i64,
+                            let ts = (v["timestamp"].as_f64().unwrap_or(0.0) * 1000.0) as i64;
+                            let conf = cls["confidence"].as_f64().unwrap_or(0.0);
+                            let presence_score = if presence { conf.max(0.0) } else { 0.0 };
+                            let breathing = vit["breathing_rate_bpm"].as_f64();
+                            let hr = vit["heart_rate_bpm"].as_f64();
+                            // #898: emit one snapshot per physical node so each
+                            // surfaces as its own Home-Assistant device (with
+                            // its own RSSI + availability). Falls back to a
+                            // single aggregate snapshot when there is no
+                            // per-node data (e.g. wifi / simulate sources).
+                            let mk = |nid: String, rssi: Option<f64>| mqtt::state::VitalsSnapshot {
+                                node_id: nid,
+                                timestamp_ms: ts,
                                 presence,
                                 motion,
-                                presence_score: if presence {
-                                    cls["confidence"].as_f64().unwrap_or(1.0)
-                                } else {
-                                    0.0
-                                },
-                                breathing_rate_bpm: vit["breathing_rate_bpm"].as_f64(),
-                                heartrate_bpm: vit["heart_rate_bpm"].as_f64(),
+                                presence_score,
+                                breathing_rate_bpm: breathing,
+                                heartrate_bpm: hr,
                                 n_persons,
-                                rssi_dbm: v["nodes"][0]["rssi_dbm"].as_f64(),
-                                vital_confidence: cls["confidence"].as_f64().unwrap_or(0.0),
+                                rssi_dbm: rssi,
+                                vital_confidence: conf,
                                 ..Default::default()
                             };
-                            let _ = vtx.send(snap);
+                            match v["nodes"].as_array() {
+                                Some(arr) if !arr.is_empty() => {
+                                    for node in arr {
+                                        let n = node["node_id"].as_u64().unwrap_or(0);
+                                        let nid = format!("{node_id}-node{n}");
+                                        let _ = vtx.send(mk(nid, node["rssi_dbm"].as_f64()));
+                                    }
+                                }
+                                _ => {
+                                    let _ = vtx.send(mk(
+                                        node_id.clone(),
+                                        v["nodes"][0]["rssi_dbm"].as_f64(),
+                                    ));
+                                }
+                            }
                         }
                     });
                     tracing::info!("MQTT publisher started -> {host}:{port}");

v2/crates/wifi-densepose-sensing-server/src/mqtt/publisher.rs

@@ -117,6 +117,23 @@ impl OwnedDiscoveryBuilder {
             via_device: self.via_device.as_deref(),
         }
     }
+
+    /// Derive a per-node builder from this base (issue #898). Each physical
+    /// RuView node must surface as its own Home-Assistant device — the base
+    /// builder's `node_id` (the MQTT client id) is replaced with the actual
+    /// node id, giving a distinct `wifi_densepose_<node>` device identifier
+    /// and a per-node friendly name, instead of collapsing every node into a
+    /// single hard-coded device.
+    pub fn for_node(&self, node_id: &str) -> OwnedDiscoveryBuilder {
+        OwnedDiscoveryBuilder {
+            discovery_prefix: self.discovery_prefix.clone(),
+            node_id: node_id.to_string(),
+            node_friendly_name: Some(format!("RuView node {node_id}")),
+            sw_version: self.sw_version.clone(),
+            model: self.model.clone(),
+            via_device: self.via_device.clone(),
+        }
+    }
 }
 
 /// Core run loop. Pumps the broadcast channel + the MQTT event loop in
@@ -129,20 +146,19 @@ async fn run(
     let opts = build_mqtt_options(&cfg);
     let (client, mut eventloop): (AsyncClient, EventLoop) = AsyncClient::new(opts, 256);
 
-    let builder_borrowed = builder_owned.as_borrowed();
     let entities = DiscoveryBuilder::enabled_entities(
         cfg.privacy_mode,
         cfg.publish_pose,
         &[], // no_semantic — wire from cli::Args in P3.5
     );
 
-    if let Err(e) = publish_all_discovery(&client, &builder_borrowed, &entities).await {
-        warn!("[mqtt] initial discovery publish failed: {e}");
-    }
-    let avail = NodeAvailability::for_builder(&builder_borrowed, &entities);
-    if let Err(e) = publish_availability(&client, &avail, "online").await {
-        warn!("[mqtt] initial availability publish failed: {e}");
-    }
+    // #898: one Home-Assistant device per node. Discovery + availability are
+    // published lazily the first time a snapshot for a given node_id arrives;
+    // each node's builder + availability are retained here for heartbeats and
+    // the offline LWT. (Previously a single hard-coded builder collapsed every
+    // node into one device.)
+    let mut nodes: std::collections::HashMap<String, (OwnedDiscoveryBuilder, NodeAvailability)> =
+        std::collections::HashMap::new();
 
     let mut rate_limiter = RateLimiter::new();
     let mut last_heartbeat = Instant::now();
@@ -179,14 +195,20 @@ async fn run(
             // Periodic heartbeat / discovery refresh.
             _ = tokio::time::sleep(Duration::from_secs(1)) => {
                 if last_heartbeat.elapsed() >= AVAILABILITY_HEARTBEAT {
-                    if let Err(e) = publish_availability(&client, &avail, "online").await {
-                        warn!("[mqtt] heartbeat publish failed: {e}");
+                    for (_, na) in nodes.values() {
+                        if let Err(e) = publish_availability(&client, na, "online").await {
+                            warn!("[mqtt] heartbeat publish failed: {e}");
+                        }
                     }
                     last_heartbeat = Instant::now();
                 }
                 if last_refresh.elapsed() >= Duration::from_secs(cfg.refresh_secs) {
-                    if let Err(e) = publish_all_discovery(&client, &builder_borrowed, &entities).await {
-                        warn!("[mqtt] discovery refresh failed: {e}");
+                    for (nb, _) in nodes.values() {
+                        if let Err(e) =
+                            publish_all_discovery(&client, &nb.as_borrowed(), &entities).await
+                        {
+                            warn!("[mqtt] discovery refresh failed: {e}");
+                        }
                     }
                     last_refresh = Instant::now();
                 }
@@ -197,18 +219,39 @@ async fn run(
                 match recv {
                     Ok(snap) => {
                         let elapsed = start_instant.elapsed();
-                        publish_snapshot(&client, &builder_borrowed, &snap, &cfg, &mut rate_limiter, elapsed).await;
+                        // #898: on first sight of a node_id, publish that
+                        // node's discovery + availability; then route its
+                        // state to per-node topics.
+                        if !nodes.contains_key(&snap.node_id) {
+                            let nb = builder_owned.for_node(&snap.node_id);
+                            let borrowed = nb.as_borrowed();
+                            if let Err(e) =
+                                publish_all_discovery(&client, &borrowed, &entities).await
+                            {
+                                warn!("[mqtt] node {} discovery failed: {e}", snap.node_id);
+                            }
+                            let na = NodeAvailability::for_builder(&borrowed, &entities);
+                            if let Err(e) = publish_availability(&client, &na, "online").await {
+                                warn!("[mqtt] node {} availability failed: {e}", snap.node_id);
+                            }
+                            nodes.insert(snap.node_id.clone(), (nb, na));
+                        }
+                        let borrowed = nodes[&snap.node_id].0.as_borrowed();
+                        publish_snapshot(&client, &borrowed, &snap, &cfg, &mut rate_limiter, elapsed).await;
                     }
                     Err(broadcast::error::RecvError::Lagged(n)) => {
                         warn!("[mqtt] lagged behind broadcast by {n} messages — dropped");
                     }
                     Err(broadcast::error::RecvError::Closed) => {
                         info!("[mqtt] broadcast channel closed, draining");
-                        // Publish offline before exit.
-                        let _ = publish_availability(&client, &avail, "offline").await;
+                        // Publish offline for every known node before exit.
+                        for (_, na) in nodes.values() {
+                            let _ = publish_availability(&client, na, "offline").await;
+                        }
                         let _ = client.disconnect().await;
                         return;
                     }
+
                 }
             }
         }
@@ -296,3 +339,52 @@ async fn publish_state(client: &AsyncClient, m: &StateMessage) -> Result<(), Cli
     };
     client.publish(&m.topic, qos, m.retain, m.payload.clone()).await
 }
+
+#[cfg(test)]
+mod per_node_device_tests {
+    //! Issue #898 — each physical node must surface as its own Home-Assistant
+    //! device, not collapse into one hard-coded device.
+    use super::*;
+
+    fn base() -> OwnedDiscoveryBuilder {
+        OwnedDiscoveryBuilder {
+            discovery_prefix: "homeassistant".into(),
+            node_id: "wifi-densepose-1".into(),
+            node_friendly_name: Some("RuView".into()),
+            sw_version: "0.0.0".into(),
+            model: "test".into(),
+            via_device: None,
+        }
+    }
+
+    fn device_identifiers(b: &OwnedDiscoveryBuilder) -> Vec<String> {
+        b.as_borrowed().build(EntityKind::Presence).device.identifiers
+    }
+
+    #[test]
+    fn for_node_overrides_node_id_and_friendly_name() {
+        let n = base().for_node("node-A");
+        assert_eq!(n.node_id, "node-A");
+        assert_eq!(n.node_friendly_name.as_deref(), Some("RuView node node-A"));
+    }
+
+    #[test]
+    fn distinct_nodes_yield_distinct_ha_device_identifiers() {
+        let b = base();
+        let a = device_identifiers(&b.for_node("node-A"));
+        let c = device_identifiers(&b.for_node("node-B"));
+        assert_eq!(a, vec!["wifi_densepose_node-A".to_string()]);
+        assert_eq!(c, vec!["wifi_densepose_node-B".to_string()]);
+        assert_ne!(a, c, "#898: two nodes must not collapse into one device");
+    }
+
+    #[test]
+    fn single_node_keeps_a_stable_identity() {
+        // Two snapshots from the same node map to the same device.
+        let b = base();
+        assert_eq!(
+            device_identifiers(&b.for_node("node-7")),
+            device_identifiers(&b.for_node("node-7"))
+        );
+    }
+}

v2/crates/wifi-densepose-sensing-server/tests/mqtt_integration.rs

@@ -171,12 +171,28 @@ async fn discovery_topics_appear_on_broker() {
     // Spawn the publisher.
     let cfg = make_cfg(port, false, "discovery");
     let builder = make_builder("inttest1");
-    let (_tx, rx) = broadcast::channel::<VitalsSnapshot>(32);
+    let (tx, rx) = broadcast::channel::<VitalsSnapshot>(32);
     let _handle = spawn(cfg, builder, rx);
 
+    // #898: discovery is now published per-node the first time a snapshot for
+    // that node_id arrives (not eagerly at startup). Drive snapshots for
+    // "inttest1" throughout the window so its device's discovery lands — same
+    // pattern as state_messages_published_on_snapshot_broadcast.
+    let tx_bg = tx.clone();
+    let drive = tokio::spawn(async move {
+        for _ in 0..60 {
+            let _ = tx_bg.send(VitalsSnapshot {
+                node_id: "inttest1".into(),
+                ..Default::default()
+            });
+            tokio::time::sleep(Duration::from_millis(200)).await;
+        }
+    });
+
     // Drain the subscriber for up to 6 s — enough for initial discovery
     // + first availability publication.
     let msgs = collect_published(&mut sub_loop, Duration::from_secs(6)).await;
+    drive.abort();
     let _ = sub.disconnect().await;
 
     // Assertions: at least the presence + heart_rate + fall discovery
@@ -221,10 +237,23 @@ async fn privacy_mode_suppresses_biometric_discovery() {
 
     let cfg = make_cfg(port, /* privacy_mode = */ true, "privacy");
     let builder = make_builder("inttest2");
-    let (_tx, rx) = broadcast::channel::<VitalsSnapshot>(32);
+    let (tx, rx) = broadcast::channel::<VitalsSnapshot>(32);
     let _handle = spawn(cfg, builder, rx);
 
+    // #898: per-node discovery is triggered by a snapshot for that node_id.
+    let tx_bg = tx.clone();
+    let drive = tokio::spawn(async move {
+        for _ in 0..60 {
+            let _ = tx_bg.send(VitalsSnapshot {
+                node_id: "inttest2".into(),
+                ..Default::default()
+            });
+            tokio::time::sleep(Duration::from_millis(200)).await;
+        }
+    });
+
     let msgs = collect_published(&mut sub_loop, Duration::from_secs(6)).await;
+    drive.abort();
     let _ = sub.disconnect().await;
 
     let topics: Vec<&str> = msgs.iter().map(|(t, _, _)| t.as_str()).collect();