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6 Commits
v2297 ... v2400

Author SHA1 Message Date
rUv
b742eae7d6 fix(sensing): fuse only coherent frame cohorts (#1726) 2026-08-27 10:10:31 -04:00
rUv
d42c5581f3 feat(rufield): ultrasonic as the field surface's second modality (#1716)
ADR-262 §8 question 5 left the second modality open, asking whether it should
be rvcsi. This answers ultrasonic instead, because the cost collapsed:
rufield-adapters now ships UltrasonicReplayAdapter, the first adapter for
Modality::Ultrasonic (registry code 7, empty since v0.1), which parses,
validates and signs BatVu range profiles upstream. RuView only has to decide
what it will put on a wire.

Bumps vendor/rufield 43b1df3 -> 9955672. Two struct literals in bridge.rs gain
fields added upstream (Observation: track_id, attributes, identity_evidence,
channel_sounding_provenance; SensorDescriptor: coordinate_frame, position_m,
orientation_xyzw). All left empty, each for a stated reason rather than a
convenient default — the pose fields in particular, because a CSI link has no
boresight and §6 makes no validated room-coordinate claim. The nine existing
P1 gates pass unchanged.

The decision this module makes is structural rather than a runtime refusal.
The adapter's full per-bin frame is P0 and would be dropped by the egress gate
after all the work of parsing and signing it; its 32-bin coarse reduction is
P1 and egress-safe. So the module does not offer the choice — it configures
the coarse mode, because a consumer cannot un-coarsen a coarse profile whereas
a check can be reordered. The gate still runs and is asserted to drop nothing.

12 gates in tests/ultrasonic_gates.rs, including the honest negative result: an
ultrasonic scan produces no fused inferences at all, and both independent
reasons are pinned. The adapter declines to populate `presence` — one
transducer pair cannot distinguish a person from a coat over the back of a
chair — and the engine's feature vocabulary is entirely statements about a
body, so range_m has nothing to drive.

The fixture is BatVu's own emitter output, byte-identical to the one in
ruvnet/rufield, so schema drift fails a build in one of three repositories
rather than an ingest in a deployment.

Not wired into the running server; P1 shipped as a library before P3 wired it
in, and this follows the same staging.
2026-08-25 21:40:53 -04:00
rUv
0df48df7b2 feat: add native iPhone LiDAR sensor and web viewer (#1684)
* feat(ios): add RuView LiDAR frame protocol

* feat(ios): capture ARKit scene depth for RuView

* feat(ios): stream compact LiDAR frames over websocket

* feat(ios): add native LiDAR capture UI

* feat(ios): add RuView LiDAR app entrypoint

* feat(web): add LiDAR bridge web package

* feat(web): decode RuView LiDAR wire frames

* feat(web): add local LiDAR websocket relay

* feat(web): add LiDAR browser viewer

* feat(web): render live LiDAR point cloud

* fix(ios): use wall clock time for LiDAR provenance

* feat(web): style LiDAR viewer

* test(web): add LiDAR codec tests

* docs: add iPhone LiDAR integration guide

* docs(adr): define iPhone LiDAR sensor bridge

* fix(ios): harden and validate LiDAR bridge

* fix(ios): qualify LiDAR wire depth type
2026-08-22 18:06:16 -04:00
rUv
bd110e0eac fix(homecore): enable standalone Arc serialization (#1682) 2026-08-22 15:55:36 -04:00
rUv
f3c361efd1 fix: align multistatic CSI time and clear Rust advisories (#1669)
Use mesh-aligned capture timestamps, remediate Rust advisories, harden the audit gate, and correct deployment claims. Includes the live MQTT subscriber lifetime fix verified against Mosquitto.
2026-08-22 14:59:22 -04:00
rUv
a3b6e1d500 docs(harness): publish final Cognitum Spaces evidence (#1653) 2026-08-19 14:52:09 -04:00
57 changed files with 2855 additions and 1003 deletions

70
.github/workflows/iphone-lidar.yml vendored Normal file
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@@ -0,0 +1,70 @@
name: iPhone LiDAR integration
on:
push:
branches: [main]
paths:
- 'integrations/iphone-lidar/**'
- 'docs/adr/ADR-340-iphone-lidar-sensor-bridge.md'
- '.github/workflows/iphone-lidar.yml'
pull_request:
paths:
- 'integrations/iphone-lidar/**'
- 'docs/adr/ADR-340-iphone-lidar-sensor-bridge.md'
- '.github/workflows/iphone-lidar.yml'
permissions:
contents: read
jobs:
web:
name: Node relay and codec
runs-on: ubuntu-latest
defaults:
run:
working-directory: integrations/iphone-lidar/web
steps:
- name: Checkout code
uses: actions/checkout@11d5960a326750d5838078e36cf38b85af677262
- name: Set up Node
uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020
with:
node-version: '22'
cache: npm
cache-dependency-path: integrations/iphone-lidar/web/package-lock.json
- name: Install dependencies
run: npm ci --ignore-scripts
- name: Run tests
run: npm test
- name: Audit runtime dependencies
run: npm audit --omit=optional --audit-level=high
ios:
name: iOS 17 compile
runs-on: macos-15
steps:
- name: Checkout code
uses: actions/checkout@11d5960a326750d5838078e36cf38b85af677262
- name: Compile native sources with strict concurrency
shell: bash
run: |
set -euo pipefail
sdk="$(xcrun --sdk iphoneos --show-sdk-path)"
build_dir="$RUNNER_TEMP/ruview-lidar-build"
mkdir -p "$build_dir"
cd "$build_dir"
xcrun swiftc \
-parse-as-library \
-target arm64-apple-ios17.0 \
-sdk "$sdk" \
-module-name RuViewLiDAR \
-strict-concurrency=complete \
-warnings-as-errors \
-emit-module \
-emit-module-path "$build_dir/RuViewLiDAR.swiftmodule" \
-c "$GITHUB_WORKSPACE"/integrations/iphone-lidar/native/RuViewLiDAR/*.swift

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@@ -14,6 +14,33 @@ env:
PYTHON_VERSION: '3.11'
jobs:
# Rust dependency advisories are deterministic for the checked-in lockfile,
# so this job gates the PR and retains the exact machine-readable report.
rust-audit:
name: Rust Dependency Audit
runs-on: ubuntu-latest
permissions:
contents: read
steps:
- name: Checkout code
uses: actions/checkout@11d5960a326750d5838078e36cf38b85af677262 # v4
- name: Install cargo-audit
run: cargo install cargo-audit --locked --version 0.22.2
- name: Audit the checked-in Rust lockfile
run: |
set -o pipefail
cargo audit --file v2/Cargo.lock --json | tee v2/cargo-audit.json
- name: Upload Rust advisory report
uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4
if: always()
with:
name: cargo-audit-report
path: v2/cargo-audit.json
if-no-files-found: error
# Static Application Security Testing (SAST)
sast:
name: Static Application Security Testing

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@@ -28,6 +28,7 @@ on:
- 'v2/crates/wifi-densepose-wifiscan/**'
- 'v2/crates/wifi-densepose-bfld/**'
- 'v2/crates/cog-ha-matter/**'
- 'v2/crates/homecore*/**'
- 'v2/Cargo.toml'
- 'v2/Cargo.lock'
- 'ui/**'

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@@ -245,8 +245,8 @@ See the measured benchmarks, witness records, and one-command reproducibility ch
|------|-------|---------|
| **MM-Fi pose model (SOTA)** | [`ruvnet/wifi-densepose-mmfi-pose`](https://huggingface.co/ruvnet/wifi-densepose-mmfi-pose) | 82.69% torso-PCK@20 (single) · 83.59% (ensemble+TTA) · 75K-param micro variant 74.30% |
| **AetherArena benchmark Space** | [`ruvnet/aether-arena`](https://huggingface.co/spaces/ruvnet/aether-arena) | self-correcting, auditable MM-Fi leaderboard |
| **Full MM-Fi study (honest picture)** | [`docs/benchmarks/mmfi-wifi-sensing-study.md`](docs/benchmarks/mmfi-wifi-sensing-study.md) | pose + action; zero-shot cross-subject ~64%, +~30 s in-room calibration → 72.2% |
| **Efficiency frontier** | [`docs/benchmarks/wifi-pose-efficiency-frontier.md`](docs/benchmarks/wifi-pose-efficiency-frontier.md) | SOTA-beating WiFi pose in a 20 KB int4 edge model |
| **Full MM-Fi study (honest picture)** | [`docs/benchmarks/mmfi-wifi-sensing-study.md`](docs/benchmarks/mmfi-wifi-sensing-study.md) | pose + action; zero-shot cross-subject ~64%, labeled in-room calibration → 72.2% |
| **Efficiency frontier** | [`docs/benchmarks/wifi-pose-efficiency-frontier.md`](docs/benchmarks/wifi-pose-efficiency-frontier.md) | SOTA-beating MM-Fi pose in a ~37 KB int4 model; live ESP32 compatibility not established |
| **Pretrained encoder** | [`ruvnet/wifi-densepose-pretrained`](https://huggingface.co/ruvnet/wifi-densepose-pretrained) | 82.3% held-out temporal-triplet, 8 KB int4 |
| **Reproducible proof (Trust Kill Switch)** | [`archive/v1/data/proof/verify.py`](archive/v1/data/proof/verify.py) + [`expected_features.sha256`](archive/v1/data/proof/expected_features.sha256) | one-command deterministic pipeline replay (SHA-256 of output vs published hash) |
| **Benchmark-proof ADR** | [ADR-168](docs/adr/ADR-168-benchmark-proof.md) | how the numbers are produced and verified |
@@ -488,12 +488,20 @@ Neural Network: processed signals → 17 body keypoints + vital signs + room mod
Output: real-time pose, breathing, heart rate, room fingerprint, drift alerts
```
No training cameras required — the [Self-Learning system (ADR-024)](docs/adr/ADR-024-contrastive-csi-embedding-model.md) bootstraps from raw WiFi data alone. [MERIDIAN (ADR-027)](docs/adr/ADR-027-cross-environment-domain-generalization.md) ensures the model works in any room, not just the one it trained in.
The [Self-Learning system (ADR-024)](docs/adr/ADR-024-contrastive-csi-embedding-model.md) provides
camera-free representation-learning components. Cross-room pose remains a separate, data-gated
problem: [MERIDIAN (ADR-027)](docs/adr/ADR-027-cross-environment-domain-generalization.md) is
**Proposed**, while the measured calibration reference requires labeled CSI/keypoint pairs and
model-specific adapters. See the [model compatibility boundary](docs/user-guide.md#model-and-capture-compatibility).
---
## 🏢 Use Cases & Applications
> **Safety boundary:** these are research and prototype applications, not medical devices,
> emergency systems, or safety-certified controls. Vital-sign and pose outputs require independent
> validation on the exact hardware, room, subjects, and failure conditions before operational use.
WiFi sensing works anywhere WiFi exists. No new hardware in most cases — just software on existing access points or a $8 ESP32 add-on. Because there are no cameras, deployments avoid privacy regulations (GDPR video, HIPAA imaging) by design.
**Scaling:** Each AP distinguishes ~3-5 people (56 subcarriers). Multi-AP multiplies linearly — a 4-AP retail mesh covers ~15-20 occupants. No hard software limit; the practical ceiling is signal physics.
@@ -528,7 +536,7 @@ WiFi sensing works anywhere WiFi exists. No new hardware in most cases — just
| Use Case | What It Does | Hardware | Key Metric | Edge Module |
|----------|-------------|----------|------------|-------------|
| **Smart home automation** | Room-level presence triggers (lights, HVAC, music) that work through walls — no dead zones, no motion-sensor timeouts | 2-3 ESP32-S3 nodes ($24) | Through-wall range ~5m | [HVAC Presence](docs/edge-modules/building.md), [Lighting Zones](docs/edge-modules/building.md) |
| **Fitness & sports** | Rep counting, posture correction, breathing cadence during exercise — no wearable, no camera in locker rooms | 3+ ESP32-S3 mesh | Pose: 17 keypoints | [Breathing Sync](docs/edge-modules/exotic.md), [Gait Analysis](docs/edge-modules/medical.md) |
| **Fitness & sports research** | Explore motion and breathing cadence without a wearable or camera; reliable posture correction requires a validated compatible pose model | 3+ ESP32-S3 mesh + edge host | Prototype; no live S3 pose accuracy claim | [Breathing Sync](docs/edge-modules/exotic.md), [Gait Analysis](docs/edge-modules/medical.md) |
| **Childcare & schools** | Naptime breathing monitoring, playground headcount, restricted-area alerts — privacy-safe for minors | 2-4 ESP32-S3 per zone | Breathing: ±1 BPM | [Sleep Apnea](docs/edge-modules/medical.md), [Perimeter Breach](docs/edge-modules/security.md) |
| **Event venues & concerts** | Crowd density mapping, crush-risk detection via breathing compression, emergency evacuation flow tracking | Multi-AP mesh (4-8 APs) | Density per m² | [Customer Flow](docs/edge-modules/retail.md), [Panic Motion](docs/edge-modules/security.md) |
| **Stadiums & arenas** | Section-level occupancy for dynamic pricing, concession staffing, emergency egress flow modeling | Enterprise AP grid | 15-20 per AP mesh | [Dwell Heatmap](docs/edge-modules/retail.md), [Queue Length](docs/edge-modules/retail.md) |

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@@ -1,8 +1,14 @@
# RuView Calibration Service (reference implementation)
Turn a **shared WiFi-CSI pose base model** into a room-specific one with a **30-second labeled
calibration** and a **~11 KB per-room LoRA adapter**. This is the deployable resolution of the
cross-subject / cross-environment generalization problem (full study: [ADR-150 §3.33.6](../../docs/adr/ADR-150-rf-foundation-encoder.md)).
Fit a room-specific **~11 KB LoRA adapter** for a shared WiFi-CSI pose base from a short **labeled
capture**. This is a measured MM-Fi reference path for cross-subject / cross-environment adaptation
(full study: [ADR-150 §3.33.6](../../docs/adr/ADR-150-rf-foundation-encoder.md)); it is not proof of
plug-and-play adaptation from a live ESP32 stream.
> **Not the proposed MERIDIAN fast path.** Both producers below require paired CSI and keypoint
> labels, and their tensor shapes and adapter files are model-specific. ADR-027's automatic,
> unlabeled 10-second MERIDIAN calibration remains **Proposed** and is not implemented as an
> end-to-end deployment command.
## Why
@@ -66,8 +72,8 @@ Adapters are **model-specific**. There are two calibration producers here:
| `cog_calibrate.py` | cog **conv+MLP** (`pose_v1.safetensors`, 56×20) | `[N,56,20]` | `.safetensors` (`fc1.a`/`fc1.b`/`fc2.a`/`fc2.b`) | Rust `cog-pose-estimation run --adapter` |
```bash
# Produce a cog-format per-room adapter for the deployed Rust pose engine:
python cog_calibrate.py --base pose_v1.safetensors --data calib.npz --out room.safetensors
# Produce a cog-format per-room adapter from X:[N,56,20], Y:[N,17,2]:
python cog_calibrate.py --base pose_v1.safetensors --data cog-calib.npz --out room.safetensors
# then in the cog runtime:
cog-pose-estimation run --config <cfg> --adapter room.safetensors
```

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@@ -139,6 +139,32 @@ Implement the §3.3 mapping: `effective_class → PrivacyClass`, `cog-ha-matter`
Add an opt-in `/ws/field` endpoint (or a `field_events` array on `SensingUpdate` behind a flag) carrying the signed `FieldEvent` + a privacy badge. Add an ingest route to `rufield-viewer` (it has none today — `server.rs:63-72`) so it can replay RuView's live feed instead of only `SyntheticSim`. **Gate:** a WS integration test asserting a connected client receives a privacy-badged, signature-verifiable `FieldEvent`; a viewer test asserting the new ingest route renders a live event. The `cognitum` appliance can speak RuField by consuming this endpoint (it already runs `ruview-vitals-worker`); deferred to its own ADR.
**P4 — fusion composition + multi-modality (ARCHITECTURE, optional).**
> **Update — second modality landed as a library.** Open question 5 below asked
> whether the second modality should be `rvcsi`. It is **ultrasonic**, because
> the cost collapsed: `rufield-adapters` now ships `UltrasonicReplayAdapter`,
> the first adapter for `Modality::Ultrasonic` (registry code 7, empty since
> v0.1), which parses, validates and signs [BatVu](https://github.com/ruvnet/batvu)
> range profiles upstream. RuView only has to decide what it will put on a wire.
>
> `wifi-densepose-rufield::ultrasonic` is that decision, and it is expressed
> structurally: the adapter is configured for its 32-bin coarse output (`P1`,
> egress-safe) rather than its full per-bin frame (`P0`, edge-local), because a
> consumer cannot un-coarsen a coarse profile whereas a runtime check can be
> reordered. The `network_egress_allowed` gate still runs and is asserted to
> drop nothing.
>
> Gates: `tests/ultrasonic_gates.rs`, 12 tests — round-trip, signature-verify,
> fusion ingest, P1 on **both** tensor and observation, structural unreachability
> of P4/P5, trust-tier refusal in both directions, determinism, whole-file
> rejection of a malformed recording. Plus one asserting the honest negative
> result: **an ultrasonic scan produces no fused inferences at all**, because the
> adapter declines to populate `presence` (one transducer pair cannot tell a
> person from a coat on a chair) and the engine's feature vocabulary is entirely
> statements about a body. RuField v0.1 has no predicate for static geometry.
>
> Not wired into the running server. P1 shipped as a library before P3 wired it
> in; this follows the same staging.
Wire a second modality (cheapest: an `rvcsi`-sourced event, or recorded mmWave) into `RuFieldFusion` alongside the WiFi event, proving cross-modality fusion above ruvsense. **Gate:** a fusion test with two modalities producing ≥1 cross-modal inference, with provenance coverage 100%.
---

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@@ -1,6 +1,6 @@
# ADR-325: Cognitum Spaces activation and governed spatial exchange
- **Status**: Accepted — legacy read live; versioned hierarchy, local memory, and governed-action implementation validated on feature branches; deployment pending
- **Status**: Accepted — legacy and versioned reads, OAuth activation, local spatial memory, governed-action policy, metaharness support, and npm distribution are implemented; HTTPS production evidence is complete
- **Date**: 2026-08-17
- **Deciders**: ruv
- **Tags**: cognitum-spaces, oauth, spatial-state, privacy, ruvector, policy, autogenous
@@ -423,41 +423,56 @@ Identity metadata deliberately advertises `spaces:read` for RuView but not
publisher surface. RuView therefore has no OAuth write, command, policy-approval,
or actuator capability.
This production evidence does not claim deployment of sites/buildings/floors/
zones, entities, semantic event or alert resources, tenant-scoped RuVector
spatial history, MQTT reconciliation, governed actions, commands, or actuators.
The first three are implemented and locally validated in the 2026-08-19 feature
branches described below, but remain non-production until their workflow and
readback gates pass. Commands and actuators remain out of scope.
That receipt was for the initial flat Space slice. The following production
expansion supersedes only its hierarchy/event/alert deferral. MQTT, commands,
actuators, real-hardware accuracy, and the long-duration operational trial
remain outside the completed claim.
## Feature-branch implementation evidence (2026-08-19)
## Completed implementation and production expansion (2026-08-19)
- Cognitum API ADR-101 implements all eight `/v1/spatial` collections, coherent
transactional hierarchy checks, stable pagination, event/alert retention,
strict P2/P3 admission, API-key-only writes, and OAuth/API-key reads. The
Firestore emulator passed both the legacy and versioned verification scripts,
including cross-resource message replay denial.
- `ruview-cognitum-spaces` adds a strictly decoded, paged, read-only client for
every versioned collection. `wifi-densepose spaces --resource ...` exposes it
while preserving the legacy flat command. The focused client suite and the
CLI no-default-features test gate pass.
- The contributor metaharness now accepts `resource`, `limit`, and opaque
`cursor` on `ruview_spaces_list`, fixes the API origin, strips API-key
compatibility authority, and revalidates hierarchy/event/alert contracts.
Full metaharness, security, brain, flywheel, manifest, audit, and pack gates
pass for the `@ruvnet/ruview` 0.5.0 release candidate.
- ADR-326 adds `ruview-spatial-memory`: one RuVector HNSW index per authenticated
tenant/workspace, replay/derivation/retention gates, cascading erasure,
bounded explanations, and XChaCha20-Poly1305 snapshots with reload-verified
key rotation. Its focused crate suite passes with `SYNTHETIC` evidence.
- ADR-327 extends `ruview-policy` with typed observe/recommend/execute intents,
exact host grants, signed approvals, nonce/idempotency defense, the existing
ADR-321 assurance matrix, and signed hash-chained receipts. `spaces:read` is
explicitly denied as execution authority. Its focused crate suite passes.
- The required whole-workspace Rust command was attempted twice on Windows:
parallel compilation ended in a compiler-process stack-buffer-overrun and a
single-job retry reached the configured timeout without a source/test
diagnostic. This is not recorded as a green gate; Linux CI remains required.
- Cognitum API PRs #211 and #212 shipped the eight `/v1/spatial` collections,
transactional hierarchy integrity, stable pagination, event/alert retention,
strict P2/P3 admission, API-key-only writes, OAuth/API-key reads, and the
additive-only Firestore release authority. Function run `32279092861`
promoted active Node 22 revision `spacesapi-00005-kaf`.
- Edge PRs #214, #215, and #216 preserved canonical UUID routing, kept SQLi
denial, and removed secret-valued API-key rate selection. Gateway run
`32284410107` promoted the reviewed immutable digest to 100% production
traffic. Every versioned collection returned HTTP 200 through the public
edge; the hierarchy composite index is `READY` and both retention TTL fields
are `ACTIVE`.
- The dedicated RuView service credential was rotated to exactly
`spaces:read` and `spaces:write`; its predecessor returns 401. A non-mutating
invalid-body probe reached write validation without persisting customer data.
Other potentially affected owner keys and residual log retention remain
tracked in Cognitum API #217.
- A live RuView Authorization Code + S256 PKCE consent requested exactly
`sensing:read spaces:read`. Its in-memory token read versioned `sites` with
HTTP 200 and schema `1.0`; the verifier then revoked the temporary refresh
credential and persisted no token.
- RuView PR #1650 merged `ruview-cognitum-spaces`,
`ruview-spatial-memory`, the ADR-327 policy extension, CLI paging, and the
guarded `ruview_spaces_list` metaharness surface. PR #1651 removed stale
feature-branch guidance and refreshed the signed package manifest.
- The contributor metaharness fixes the API origin, accepts bounded resource,
limit, and opaque-cursor inputs, strips API-key compatibility authority over
MCP, invokes only the hardened OAuth CLI, and rejects raw sensing or malformed
hierarchy/event/alert output. Its test, security, reviewed-brain, flywheel,
manifest, audit, exact-tarball, and claim-check gates pass.
- Release run `32286297277` rebuilt and smoke-tested the exact package and
provenance-published `@ruvnet/ruview` 0.5.0. The public npm registry resolves
0.5.0 as `latest`; no workstation publish was used.
- `ruview-spatial-memory` keeps one RuVector HNSW index per authenticated
tenant/workspace with replay, derivation, retention, cascading-erasure,
bounded-explanation, encrypted-snapshot, and reload-verified rotation gates.
This is local `SYNTHETIC` evidence, not a production sensing claim.
- `ruview-policy` keeps observe/recommend/execute intents distinct, requires
exact host grants plus signed approval for consequence, rejects nonce replay,
and emits signed hash-chained receipts. `spaces:read` is explicitly denied as
execution authority.
- Focused Rust gates and the Linux workspace/CLI/security lanes pass. Earlier
Windows whole-workspace attempts ended in host compiler failure or timeout;
those attempts are not reclassified as green evidence.
- No OAuth write/action scope, actuator callback, MQTT deployment claim, sensing
accuracy claim, or real-hardware claim is introduced.
@@ -478,8 +493,9 @@ readback gates pass. Commands and actuators remain out of scope.
- Two credential types coexist during migration and must stay visibly distinct.
- OAuth depends on Identity JWKS availability and correct key rotation.
- Production currently exposes the legacy spaces slice; the implemented full
hierarchy/events/alerts model remains staged until deployment/readback.
- Production exposes both the legacy Space twins and the versioned hierarchy,
anonymous entities, semantic events, and alerts over HTTPS. MQTT remains a
design contract without deployment evidence.
- OAuth workspace IDs will return only documents populated with `workspaceId`;
legacy owner-only documents require an explicit migration, never a broad query.
- The RuView client exposes no write, command, or agent execution surface. The

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@@ -0,0 +1,59 @@
# ADR 340: iPhone LiDAR Sensor Bridge
Status: Proposed
## Context
RuView needs a low cost mobile geometry sensor that can contribute calibrated spatial observations without coupling the perception substrate to Apple frameworks.
ARKit exposes rear LiDAR scene depth through `ARFrame.sceneDepth` and `smoothedSceneDepth` on supported devices. Ordinary mobile web pages do not receive this ARKit depth surface directly, so native capture and web visualization must be separated.
## Decision
Use a two layer architecture.
1. Native Swift and ARKit perform acquisition.
2. A modality neutral wire frame transports geometry into browser tools and, next, the RuView HAL.
The native client will capture depth, confidence, camera intrinsics, and world tracking pose. RGB imagery is excluded from the default transport.
The protocol identifier is `ruview.lidar.depth.v1`.
Depth samples are quantized to UInt16 millimeters for transport. Confidence remains UInt8. The default sender downsamples by two spatially and caps transmission at 15 FPS. Full fidelity depth remains available locally for future on device inference.
## RuView integration boundary
The transport must not become a second world model. The production receiver converts each packet into the canonical `ruview-hal::Observation`, then passes it through authenticated sensor identity, provenance, OOD gating, uncertainty aware fusion, spatial memory, and WorldGraph adapters.
Rules:
1. `source=live` is valid only for frames produced by an active ARKit session.
2. Sequence numbers are monotonic per sensor session.
3. Wall clock timestamp is separate from ARKit monotonic frame timing.
4. RGB is off by default and requires an explicit higher privacy capability.
5. Browser clients consume geometry but are not treated as authoritative sensors.
6. Unsupported devices fail closed rather than substituting simulated depth.
## Performance target
`[SYNTHETIC]` A 256 x 192 Float32 depth map is about 196 KB before confidence and metadata. Downsampling to 128 x 96 and encoding each sample as two byte depth plus one byte confidence yields about 36.9 KB raw. At 15 FPS the raw sensor payload is about 553 KB/s. Base64 raises this to roughly 737 KB/s before JSON metadata. These values are arithmetic sizing estimates, not device measurements.
The `[CLAIMED target]` for local network latency is below 150 ms p95. A later binary WebSocket or QUIC transport can remove base64 overhead; the exact end-to-end reduction must be measured before it is claimed.
## Security
The development relay is LAN-facing, requires a random per-run bearer token, bounds message size, and restricts the files it serves. Its default `ws://` transport is not encrypted, so it is not a production trust boundary.
Production requires WSS, authenticated sensor identity, replay protection, message size limits, per tenant authorization, provenance receipts, and explicit retention policy before persistence.
## Consequences
Benefits include commodity hardware, metric depth, tracked camera pose, rapid room scanning, calibration support for RF sensing, and a practical ground truth source for RuView experiments.
The main limitation is that Apple provides processed scene depth rather than the underlying raw transient LiDAR waveform. Therefore this implementation supports direct geometry and sensor fusion now, but does not reproduce research systems that require raw multipath time of flight transients for non line of sight reconstruction.
## Acceptance criteria
A physical LiDAR capable iPhone must stream live geometry to the browser viewer with monotonically increasing sequence numbers, no RGB payload, valid confidence maps, and below 150 ms p95 local network latency over a 60 second run.
CI type-checking and simulator runs do not satisfy this criterion. Until a captured physical-device run records the environment and results, the hardware behavior and latency remain unverified.

View File

@@ -5,10 +5,15 @@ PCK@20 (MultiFormer Table VII metric: `‖predgt‖ ≤ 0.2·‖R-shoulder
The flagship [`ruvnet/wifi-densepose-mmfi-pose`](https://huggingface.co/ruvnet/wifi-densepose-mmfi-pose)
reaches **83.59%** torso-PCK@20 (vs MultiFormer 72.25%, CSI2Pose 68.41%). But the headline number
isn't the whole story for **edge deployment** — on a Raspberry Pi / ESP32-class target, *params and
isn't the whole story for **edge deployment** — on a Raspberry Pi-class edge host, *params and
latency* matter as much as accuracy. So we swept model size to map the **accuracy-per-parameter
frontier**: how small can a WiFi-CSI pose model be and still beat the prior published SOTA?
> **Hardware compatibility boundary.** These models consume MM-Fi tensors shaped
> `[3,114,10]`. Parameter size alone does not make that input, model architecture, or runtime
> compatible with an ESP32-S3/C6 capture node. The measurements below are dataset and x86/GPU
> measurements; no ESP32 inference latency or live ESP32-to-MM-Fi adapter is claimed.
## The frontier
| Model | Params | Latency (batch=1) | torso-PCK@20 | vs SOTA (72.25%) |
@@ -38,8 +43,10 @@ Size alone isn't the claim — what matters is **accuracy at the deployed precis
**The honest edge result:** `micro` is **lossless at int8 (73.5 KB, 74.70%)**, and at **int4 (36.7 KB)
naïve post-training quantization falls below SOTA (70.21%) — but quantization-aware training fully
recovers it to 74.46%**, still beating MultiFormer. So a **SOTA-beating WiFi-pose model genuinely runs
in ~37 KB int4** (with QAT) or **~73 KB int8** (no retraining) — deployable on the sensing node itself.
recovers it to 74.46%**, still beating MultiFormer. So a **SOTA-beating WiFi-pose model fits in
~37 KB int4** (with QAT) or **~73 KB int8** (no retraining). That is a model-footprint result, not
evidence that it runs on an ESP32 sensing node; a compatible capture adapter and embedded runtime
still need to be implemented and measured.
`nano` (40K params) sits at the SOTA line in fp32 and is best treated as int8.
(We also tested flagship→tiny **knowledge distillation**: it did *not* help — the tiny students reach

View File

@@ -75,7 +75,7 @@ WiFi DensePose turns commodity WiFi signals into real-time human pose estimation
| Option | Cost | Capabilities |
|--------|------|-------------|
| ESP32-S3 mesh (3-6 boards) | ~$54 | Full CSI: pose, breathing, heartbeat, presence |
| ESP32-S3 mesh (3-6 boards) | ~$54 | CSI capture for presence, motion, and vital-sign heuristics; live 17-keypoint pose remains below-target and is not a validated capability |
| Intel 5300 / Atheros AR9580 | $50-100 | Full CSI with 3x3 MIMO (Linux only) |
| Any WiFi laptop | $0 | RSSI-only: coarse presence and motion detection |
@@ -1214,6 +1214,22 @@ levels. Read the label, not the headline ([ADR-187](adr/ADR-187-archive-v1-depre
**Does it actually run, and can a single ESP32 do pose? ([#509](https://github.com/ruvnet/RuView/issues/509), [#1125](https://github.com/ruvnet/RuView/issues/1125))** Yes, it runs, and the results are reproducible: the deterministic signal-pipeline proof (`python archive/v1/data/proof/verify.py`, must print `VERDICT: PASS`), the committed pose training dump (`v2/crates/cog-pose-estimation/cog/artifacts/train_results.json`), and the auditable MM-Fi arena all back specific numbers. But a single-antenna, 56-subcarrier CSI stream at a 20-frame window does *not* carry the fine-grained spatial information the multi-antenna NIC research relies on — so the shippable pose accuracy the project stands behind today is the **MM-Fi benchmark number**, not a live single-ESP32 number. The path to a first reproducible on-device baseline (PCK@20 ≥ 35%) is tracked in [ADR-079](adr/ADR-079-camera-ground-truth-training.md) / [#645](https://github.com/ruvnet/RuView/issues/645).
### Model and capture compatibility
These artifacts share a pose objective, but not an input contract or adapter format. A checkpoint
is usable only when capture preprocessing, tensor shape, architecture, and runtime all match.
| Artifact/path | Required input | Measured status | Live ESP32 compatibility |
|---------------|----------------|-----------------|--------------------------|
| MM-Fi flagship and `micro` transformer | `[N,3,114,10]` amplitude | **MEASURED** on MM-Fi `random_split`; calibration reference is Python `.npz` LoRA | No direct S3/C6 path is validated; resampling a 56-tone SISO stream does not recreate three-antenna MM-Fi input |
| Cog `pose_v1.safetensors` | `[N,56,20]` amplitude | **MEASURED** PCK@20 = 3.0%, below the ≥35% target; cog-format LoRA is `.safetensors` | Shape matches the canonical window, but the documented live runtime remains below-target/stub and is not a reliable pose claim |
| Viewer `heuristic_pose_from_amplitude` | live canonical amplitude | Skeleton-layout placeholder, not a trained pose model | Renders a demonstrator skeleton only; it is not pose accuracy evidence |
| MERIDIAN automatic unlabeled calibration | proposed ~200-frame target-room capture | **PROPOSED** in ADR-027; no validated end-to-end command | Not available. The current calibration tools require paired CSI/keypoint labels and model-specific inputs |
Calibration files are not interchangeable: `calibrate.py` targets the MM-Fi transformer, while
`cog_calibrate.py` targets the cog conv+MLP. See the
[calibration reference](../aether-arena/calibration/README.md) for their exact schemas.
### Download
```bash
@@ -1458,7 +1474,7 @@ The pipeline runs 10 phases:
3. Subcarrier resampling (114->56 or 30->56 via Catmull-Rom interpolation)
4. Graph transformer construction (17 COCO keypoints, 16 bone edges)
5. Cross-attention training (CSI features -> body pose)
6. **Domain-adversarial training** (MERIDIAN: gradient reversal + virtual domain augmentation)
6. Experimental domain-adversarial components (MERIDIAN research modules; not a validated automatic deployment path)
7. Composite loss optimization (MSE + CE + UV + temporal + bone + symmetry)
8. SONA adaptation (micro-LoRA + EWC++)
9. Sparse inference optimization (hot/cold neuron partitioning)
@@ -1474,14 +1490,18 @@ Progressive loading enables instant startup (Layer A loads in <5ms with basic in
### Cross-Environment Adaptation (MERIDIAN)
Models trained in one room typically lose 40-70% accuracy in a new room due to different WiFi multipath patterns. The MERIDIAN system (ADR-027) solves this with a 10-second automatic calibration:
Models trained in one room can lose substantial accuracy in a new room because the multipath
distribution changes. ADR-027 proposes an automatic adaptation design, and the Rust tree contains
individual research components, but RuView does **not** currently provide a validated command that
turns ~200 unlabeled frames into a working room adapter.
1. **Deploy** the trained model in a new room
2. **Collect** ~200 unlabeled CSI frames (10 seconds at 20 Hz)
3. The system automatically generates environment-specific LoRA weights via contrastive test-time training
4. No labels, no retraining, no user intervention
Current, testable calibration is the separate **labeled** reference in
`aether-arena/calibration/`: collect paired CSI/keypoint samples, then fit a model-specific LoRA
adapter. The MM-Fi transformer expects `[N,3,114,10]`; the cog expects `[N,56,20]`. Neither adapter
loads into the other model, and neither result establishes live ESP32 pose accuracy without a
leakage-free held-out capture and mean-pose baseline.
MERIDIAN components (all pure Rust, +12K parameters):
ADR-027 research components:
| Component | What it does |
|-----------|-------------|
@@ -1489,7 +1509,7 @@ MERIDIAN components (all pure Rust, +12K parameters):
| Domain Factorizer | Separates pose-relevant from room-specific features |
| Geometry Encoder | Encodes AP positions (FiLM conditioning with DeepSets) |
| Virtual Augmentor | Generates synthetic environments for robust training |
| Rapid Adaptation | 10-second unsupervised calibration via contrastive TTT |
| Rapid Adaptation | Proposed unlabeled contrastive TTT; not wired as a validated deployment workflow |
See [ADR-027](adr/ADR-027-cross-environment-domain-generalization.md) for the full design.
@@ -1647,7 +1667,7 @@ Not every ADR-295296 remediation item is preview-only. Three are live now:
| Target | Use case | Source target flag | Notes |
|---|---|---|---|
| **ESP32-S3** (default) | Production CSI mesh, 17-keypoint pose | `idf.py set-target esp32s3` | Dual-core 240 MHz, PSRAM, native USB-OTG, DVP camera path |
| **ESP32-S3** (default) | Production CSI capture mesh; presence/motion/vital heuristics | `idf.py set-target esp32s3` | Dual-core 240 MHz, PSRAM, native USB-OTG, DVP camera path; live 17-keypoint pose is not validated |
| **ESP32-C6** ([ADR-110](adr/ADR-110-esp32-c6-firmware-extension.md)) | Wi-Fi 6 / 802.15.4 research, battery seed nodes | `idf.py set-target esp32c6` | Single-core 160 MHz, no PSRAM, 802.11ax HE PHY, 802.15.4 (Thread/Zigbee), LP-core hibernation ~5 µA |
The same `firmware/esp32-csi-node` source tree builds for both. ESP-IDF picks up `sdkconfig.defaults.esp32c6` automatically when the target is set to `esp32c6`; otherwise it uses `sdkconfig.defaults` (S3). All C6-only modules are `#ifdef`-gated, so the S3 build is byte-identical to today.
@@ -2071,7 +2091,11 @@ Pre-trained models are available on HuggingFace:
- **SOTA MM-Fi pose model** (82.69% torso-PCK@20) — https://huggingface.co/ruvnet/wifi-densepose-mmfi-pose
- **AetherArena leaderboard Space** — https://huggingface.co/spaces/ruvnet/aether-arena
Download and start sensing immediately — no datasets, no GPU, no training needed. Results are reproducible via `python archive/v1/data/proof/verify.py` (deterministic SHA-256 proof) — see [ADR-168](adr/ADR-168-benchmark-proof.md).
The encoder artifact can be downloaded for its documented inference path without retraining. The
MM-Fi pose checkpoint is benchmark evidence, not a drop-in live ESP32 model; it requires its exact
input contract and runtime described in [Model and capture compatibility](#model-and-capture-compatibility).
The deterministic signal-pipeline proof is reproducible via `python archive/v1/data/proof/verify.py`
(see [ADR-168](adr/ADR-168-benchmark-proof.md)), but that proof does not validate pose accuracy.
### Quick Start with Pre-Trained Models
@@ -2636,7 +2660,12 @@ No. Run `docker run -p 3000:3000 ruvnet/wifi-densepose:latest` and open `http://
No. Consumer WiFi exposes only RSSI (one number per access point), not CSI (56+ complex subcarrier values per frame). RSSI supports coarse presence and motion detection. Full pose estimation requires CSI-capable hardware like an ESP32-S3 ($8) or a research NIC.
**Q: How accurate is the pose estimation?**
Accuracy depends on hardware and environment. With a 3-node ESP32 mesh in a single room, the system tracks 17 COCO keypoints. The core algorithm follows the CMU "DensePose From WiFi" paper ([arXiv:2301.00250](https://arxiv.org/abs/2301.00250)). The MERIDIAN domain generalization system (ADR-027) reduces cross-environment accuracy loss from 40-70% to under 15% via 10-second automatic calibration.
The strongest published RuView result is the MM-Fi transformer benchmark (82.69% torso-PCK@20 on
the matched `random_split` protocol), not a live ESP32 result. The committed cog model measured
3.0% PCK@20 on its holdout, below the ≥35% target, and the viewer's live skeleton is a heuristic
placeholder. No measured claim currently shows a 3-node ESP32 mesh reliably tracking 17 keypoints.
ADR-027's 10-second unlabeled MERIDIAN adaptation is Proposed; the available measured calibration
reference uses labeled, model-specific samples.
**Q: Does it work through walls?**
Yes. WiFi signals penetrate non-metallic materials (drywall, wood, concrete up to ~30cm). Metal walls/doors significantly attenuate the signal. With a single AP the effective through-wall range is approximately 5 meters. With a 3-6 node multistatic mesh (ADR-029), attention-weighted cross-viewpoint fusion extends the effective range to ~8 meters through standard residential walls.

View File

@@ -3,7 +3,7 @@
"generator": "RuView metaharness provenance v2",
"template": "vertical:ruview",
"name": "@ruvnet/ruview",
"version": "0.5.0",
"version": "0.5.1",
"hosts": [
"claude-code",
"codex"
@@ -31,7 +31,7 @@
"flywheel/genome.json": "75db44a3cab70d9459fc8c07863f640ac1214bfaa243483939e1506d63f51214",
"flywheel/replay.mjs": "0670ca0b03701f4afe0b4bca8a3d58d481676b61a94a5b98c6a425aefb1159ab",
"flywheel/run.mjs": "6d4f97db16900c45367b6538848cbe1915af999e663720dfc51f2bb1698f1cd0",
"package.json": "e508476278467cbe63e836d2b42f24649393fb59ce4fe40925d4418da4e79acc",
"package.json": "5d29ef238f310c9ee5c57501ab651acc0f856f831b696ada187de71e4b5935a6",
"scripts/sync-skills.mjs": "43715dab61e204dc91bbd61755810e8fdb2f66e2b0c0bd791b4bf48a2e293565",
"scripts/update-manifest.mjs": "8f56764b8f70aed55da0c7e2417ae875b0d58d781d839b6db7f115f08af61e6b",
"scripts/verify-manifest.mjs": "6491a221762efcfeb3e749ecab243b204f17fd5bc871f3d4025597f31b8f0f10",
@@ -43,7 +43,7 @@
"skills/verify.md": "2d38d240e9810a7827e2ebd3717dc0f85c646cc92e46c3812fe77c5b9eb40b76",
"src/brain.js": "0f16a75aea943acdacc430ff11d5df7ecdec9cca2ab497795ff6f33eaebdfab6",
"src/guardrails.js": "aacc8fa6088f7f1ccea3a0b02171a5c516b95d3416ee3ba87add3879a1d6aaad",
"src/guidance.js": "beaa130b546fdb495ae8b17e52c46ca8bbe50c218f05705244922d3633125f4e",
"src/guidance.js": "583904c854eb17e98cb7d959330989c01990a71cff091515777aba8f345de1bf",
"src/hosts/claude-code.js": "2212bc39b49822018800dfe33a471e56bbb4c5233d716bfa7aa4fff77aa23edb",
"src/hosts/codex.js": "d41ecd132ce2db7b47aad9cebbc020d70e6810d48c3554858d099ff2e8f6608b",
"src/hosts/index.js": "ab276c41ab722bcdf72c2d1649cecbb760ae05c41c1372aae4c2447aa7c11539",
@@ -55,7 +55,7 @@
"src/spaces.js": "45ef786537cb2a446db5e926e5a1c10b73639d2767dec84611f914f78d4325eb",
"src/tools.js": "55960c9a677661763e0317fd54ccc787c2edb39c87371c7fbc40cd55f0761c04"
},
"filesDigest": "961357bd4458bd6fa759f0a8d5bf042c7b652dcea3700363ae25d03299aa5027",
"filesDigest": "28a3bbd9bbcf966df9fae8ec6ea5be3441f6ab535c1636bb1ce33f67b827d423",
"brainDigest": "c0fb7b079ded157059b91601361429944697dae3cc42abc00dfe1a680986b0f4",
"gateFingerprint": "6e53c784eee38310188948fc75fb49e6b4ebc04e247d01b903fa8c8a92d67bdd",
"developmentPins": {

View File

@@ -1 +1 @@
8a4cb8b2a5766455acbf936826d499ec12432e77f9c17f90526ebcdfdc08485d manifest.json
478ccaff9aa249bc7ea6e20551ccc9ac88697a3cc91a7b55400337c5e939a19e manifest.json

View File

@@ -1,12 +1,12 @@
{
"name": "@ruvnet/ruview",
"version": "0.5.0",
"version": "0.5.1",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "@ruvnet/ruview",
"version": "0.5.0",
"version": "0.5.1",
"license": "MIT",
"bin": {
"ruview": "bin/cli.js"

View File

@@ -1,6 +1,6 @@
{
"name": "@ruvnet/ruview",
"version": "0.5.0",
"version": "0.5.1",
"description": "RuView WiFi-sensing operator harness — onboard, calibrate, verify, enforce evidence guardrails, and read Cognitum Spaces through explicitly granted OAuth.",
"type": "module",
"bin": {

View File

@@ -250,7 +250,7 @@ const CAPABILITIES = Object.freeze([
'The projection is read-only and grants no write, pairing, command, policy-approval, or actuator authority.',
'MCP requires the credential-use grant; bearer tokens and API keys are never accepted as tool arguments.',
'OAuth refresh may rotate the local credential file before a read returns.',
'Production evidence covers the legacy flat Spaces read. Versioned collections, spatial memory, and governed actions remain staged until workflow deployment/readback.',
'Production evidence covers legacy and versioned HTTPS reads. Spatial memory remains tenant/workspace-local, while governed actions remain separately policy-gated; neither expands OAuth authority.',
'Persistent memory is local tenant/workspace state and governed actions expose authorization receipts only; neither expands OAuth authority.',
],
},

View File

@@ -0,0 +1,78 @@
# RuView iPhone LiDAR
This experimental integration provides the native and browser components needed to use a LiDAR-capable iPhone as a RuView geometry sensor. The native source is type-checked against the iOS SDK in CI; physical-device validation is tracked separately below.
## Architecture
```text
iPhone LiDAR
-> ARKit sceneDepth
-> depth + confidence + camera intrinsics + device pose
-> compact u16 millimeter wire frame
-> WebSocket relay
-> browser point cloud
-> future RuView HAL / fusion ingest
```
The native path is the sensor. The web path is a receiver and visualization surface. Mobile Safari does not expose ARKit scene depth directly to ordinary web pages, so the browser cannot replace the native capture layer on iPhone today.
## Native iPhone path
Create an iOS SwiftUI app target in Xcode, deployment target iOS 17 or newer, then add the files under `native/RuViewLiDAR/` to the target.
Add this Info.plist value:
```xml
<key>NSCameraUsageDescription</key>
<string>RuView uses the camera and LiDAR scanner to capture local depth geometry.</string>
```
Run on a physical LiDAR capable iPhone or iPad. The simulator does not provide LiDAR scene depth.
The app requests `ARWorldTrackingConfiguration` with `.sceneDepth`, checks `supportsFrameSemantics`, extracts `ARDepthData.depthMap` and `confidenceMap`, and never transmits RGB camera frames.
## Browser path
```bash
cd integrations/iphone-lidar/web
npm ci
npm test
npm start
```
The relay prints a random per-run access token. Open the printed browser URL and set the iPhone endpoint to the printed native URL. They have this form:
```text
http://HOST:8787/?token=TOKEN
ws://HOST:8787/ws/lidar?token=TOKEN
```
Set `RUVIEW_LIDAR_TOKEN` to supply the token explicitly. The token only prevents unauthenticated peers from joining the development relay; because `ws://` does not encrypt it, production use requires TLS and `wss://`.
## Wire format
Schema: `ruview.lidar.depth.v1`
Depth is downsampled by 2 in each dimension by default and streamed at a maximum of 15 FPS. Each depth sample is encoded as little endian UInt16 millimeters plus one UInt8 confidence value. `[SYNTHETIC]` Arithmetic sizing reduces the depth payload from roughly 196 KB per 256 x 192 Float32 frame to roughly 37 KB per 128 x 96 frame before base64 and JSON overhead.
`[SYNTHETIC]` At 15 FPS that is approximately 0.75 MB/s after base64 overhead, versus roughly 8 MB/s for uncompressed Float32 JSON at full resolution. These are sizing estimates, not device or network measurements.
## Privacy and governance
The initial implementation labels provenance as `source=live` and `privacyClass=geometry-only`. It sends depth geometry, confidence, camera intrinsics, pose, sequence, and wall clock timestamp. It does not send RGB imagery.
The development relay requires an ephemeral token and bounds each WebSocket message, but it is not a production trust boundary. Production integration should terminate the WebSocket inside RuView, authenticate the device using the existing sensor identity path, convert each frame into `ruview-hal::Observation`, and attach witness receipts before fusion or persistence.
## Validation status
- `[MEASURED]` The committed Node tests cover wire decoding, malformed inputs, relay authentication, static-file restrictions, and live WebSocket forwarding.
- `[MEASURED]` GitHub Actions type-checks the native sources with strict concurrency against the iOS 17 SDK.
- Physical iPhone capture, end-to-end rendering, confidence-map behavior, and the latency target are not yet measured. A simulator or CI compile does not satisfy the hardware acceptance test.
## Acceptance test
1. Run the relay and browser viewer.
2. Run the native app on a LiDAR capable iPhone.
3. Start LiDAR capture and enable streaming.
4. Move the phone through a room.
5. Verify the browser shows a changing point cloud, sequence increases monotonically, latency stays below the `[CLAIMED target]` of 150 ms p95 on a local WiFi network, and no RGB payload is present in captured WebSocket frames.

View File

@@ -0,0 +1,121 @@
import SwiftUI
struct ContentView: View {
@StateObject private var capture = LiDARCaptureManager()
@State private var endpoint = "ws://HOST:8787/ws/lidar?token=TOKEN"
@State private var streaming = false
@State private var status = "Idle"
private let streamer = WebSocketStreamer()
var body: some View {
NavigationStack {
Form {
Section("Sensor") {
HStack {
Text("State")
Spacer()
Text(stateText)
.foregroundStyle(stateColor)
}
HStack {
Text("Capture FPS")
Spacer()
Text(capture.framesPerSecond.formatted(.number.precision(.fractionLength(1))))
}
if let frame = capture.lastFrame {
HStack {
Text("Depth")
Spacer()
Text("\(frame.depth.width) x \(frame.depth.height)")
}
HStack {
Text("Sequence")
Spacer()
Text("\(frame.provenance.sequence)")
}
}
Button("Start LiDAR") {
capture.start(smoothed: false)
}
.disabled(capture.state == .running)
Button("Stop") {
capture.stop()
}
.disabled(capture.state != .running)
}
Section("RuView Stream") {
TextField("ws://host:port/ws/lidar", text: $endpoint)
.textInputAutocapitalization(.never)
.autocorrectionDisabled()
Toggle("Stream geometry", isOn: $streaming)
.onChange(of: streaming) { _, enabled in
Task {
if enabled {
do {
try await streamer.connect(to: endpoint)
status = "Connected"
} catch {
streaming = false
status = error.localizedDescription
}
} else {
await streamer.disconnect()
status = "Disconnected"
}
}
}
Text(status)
.font(.caption)
.foregroundStyle(.secondary)
}
Section("Privacy") {
Text("This implementation transmits depth geometry, confidence, camera intrinsics, and device pose. RGB camera frames are not transmitted.")
.font(.footnote)
}
}
.navigationTitle("RuView LiDAR")
.onAppear {
capture.onFrame = { frame in
guard streaming else { return }
Task {
do {
try await streamer.send(frame, maxFPS: 15, sampleStep: 2)
} catch {
await MainActor.run {
status = error.localizedDescription
}
}
}
}
}
.onDisappear {
capture.stop()
Task { await streamer.disconnect() }
}
}
}
private var stateText: String {
switch capture.state {
case .idle: return "Idle"
case .unsupported: return "No LiDAR"
case .running: return "Live"
case .failed(let message): return "Error: \(message)"
}
}
private var stateColor: Color {
switch capture.state {
case .running: return .green
case .failed, .unsupported: return .red
case .idle: return .secondary
}
}
}

View File

@@ -0,0 +1,138 @@
import ARKit
import CoreVideo
import Foundation
@MainActor
final class LiDARCaptureManager: NSObject, ObservableObject {
enum State: Equatable {
case idle
case unsupported
case running
case failed(String)
}
@Published private(set) var state: State = .idle
@Published private(set) var lastFrame: RuViewLiDARFrame?
@Published private(set) var framesPerSecond: Double = 0
let session = ARSession()
var onFrame: (@MainActor @Sendable (RuViewLiDARFrame) -> Void)?
private var sequence: UInt64 = 0
private var lastTimestamp: TimeInterval?
private let processingQueue = DispatchQueue(label: "one.ruv.lidar.capture", qos: .userInitiated)
override init() {
super.init()
session.delegate = self
session.delegateQueue = processingQueue
}
func start(smoothed: Bool = false) {
let configuration = ARWorldTrackingConfiguration()
let semantic: ARConfiguration.FrameSemantics = smoothed ? .smoothedSceneDepth : .sceneDepth
guard ARWorldTrackingConfiguration.supportsFrameSemantics(semantic) else {
state = .unsupported
return
}
configuration.frameSemantics.insert(semantic)
configuration.worldAlignment = .gravity
session.run(configuration, options: [.resetTracking, .removeExistingAnchors])
state = .running
}
func stop() {
session.pause()
state = .idle
}
nonisolated private func makeFrame(from frame: ARFrame) -> RuViewLiDARFrame? {
guard let sceneDepth = frame.sceneDepth ?? frame.smoothedSceneDepth else { return nil }
let depthMap = sceneDepth.depthMap
let confidenceMap = sceneDepth.confidenceMap
guard CVPixelBufferLockBaseAddress(depthMap, .readOnly) == kCVReturnSuccess else {
return nil
}
defer { CVPixelBufferUnlockBaseAddress(depthMap, .readOnly) }
guard CVPixelBufferGetPixelFormatType(depthMap) == kCVPixelFormatType_DepthFloat32,
let depthBase = CVPixelBufferGetBaseAddress(depthMap) else {
return nil
}
let width = CVPixelBufferGetWidth(depthMap)
let height = CVPixelBufferGetHeight(depthMap)
let stride = CVPixelBufferGetBytesPerRow(depthMap) / MemoryLayout<Float>.size
let pointer = depthBase.assumingMemoryBound(to: Float.self)
var meters = [Float]()
meters.reserveCapacity(width * height)
for y in 0..<height {
let row = pointer.advanced(by: y * stride)
for x in 0..<width {
let value = row[x]
meters.append(value.isFinite && value > 0 ? value : 0)
}
}
var confidence = [UInt8](repeating: 0, count: width * height)
if let confidenceMap,
CVPixelBufferGetPixelFormatType(confidenceMap) == kCVPixelFormatType_OneComponent8,
CVPixelBufferGetWidth(confidenceMap) == width,
CVPixelBufferGetHeight(confidenceMap) == height,
CVPixelBufferLockBaseAddress(confidenceMap, .readOnly) == kCVReturnSuccess {
defer { CVPixelBufferUnlockBaseAddress(confidenceMap, .readOnly) }
if let confidenceBase = CVPixelBufferGetBaseAddress(confidenceMap) {
let confidenceStride = CVPixelBufferGetBytesPerRow(confidenceMap)
let confidencePointer = confidenceBase.assumingMemoryBound(to: UInt8.self)
for y in 0..<height {
let row = confidencePointer.advanced(by: y * confidenceStride)
for x in 0..<width {
confidence[y * width + x] = row[x]
}
}
}
}
return RuViewLiDARFrame(
intrinsics: frame.camera.intrinsics,
imageResolution: frame.camera.imageResolution,
cameraTransform: frame.camera.transform,
depthWidth: width,
depthHeight: height,
depthMeters: meters,
confidence: confidence,
sequence: 0,
timestamp: Date().timeIntervalSince1970
)
}
}
extension LiDARCaptureManager: ARSessionDelegate {
nonisolated func session(_ session: ARSession, didUpdate frame: ARFrame) {
guard let base = makeFrame(from: frame) else { return }
let frameTimestamp = frame.timestamp
Task { @MainActor in
sequence &+= 1
let corrected = base.assigningSequence(sequence)
if let previous = lastTimestamp {
let delta = frameTimestamp - previous
if delta > 0 { framesPerSecond = 1.0 / delta }
}
lastTimestamp = frameTimestamp
lastFrame = corrected
onFrame?(corrected)
}
}
nonisolated func session(_ session: ARSession, didFailWithError error: Error) {
Task { @MainActor in
state = .failed(error.localizedDescription)
}
}
}

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import Foundation
import simd
struct RuViewLiDARFrame: Codable, Sendable {
struct Intrinsics: Codable, Sendable {
let fx: Float
let fy: Float
let cx: Float
let cy: Float
let imageWidth: Int
let imageHeight: Int
}
struct Pose: Codable, Sendable {
let matrix: [Float]
}
struct Depth: Codable, Sendable {
let width: Int
let height: Int
let meters: [Float]
let confidence: [UInt8]
}
struct Provenance: Codable, Sendable {
let sensor: String
let source: String
let privacyClass: String
let sequence: UInt64
let timestampNs: UInt64
let schema: String
}
let type: String
let intrinsics: Intrinsics
let pose: Pose
let depth: Depth
let provenance: Provenance
init(
intrinsics: simd_float3x3,
imageResolution: CGSize,
cameraTransform: simd_float4x4,
depthWidth: Int,
depthHeight: Int,
depthMeters: [Float],
confidence: [UInt8],
sequence: UInt64,
timestamp: TimeInterval
) {
self.type = "ruview.lidar.depth.v1"
self.intrinsics = Intrinsics(
fx: intrinsics.columns.0.x,
fy: intrinsics.columns.1.y,
cx: intrinsics.columns.2.x,
cy: intrinsics.columns.2.y,
imageWidth: Int(imageResolution.width),
imageHeight: Int(imageResolution.height)
)
self.pose = Pose(matrix: cameraTransform.columnMajorArray)
self.depth = Depth(
width: depthWidth,
height: depthHeight,
meters: depthMeters,
confidence: confidence
)
self.provenance = Provenance(
sensor: "apple-arkit-scene-depth",
source: "live",
privacyClass: "geometry-only",
sequence: sequence,
timestampNs: UInt64(max(0, timestamp) * 1_000_000_000),
schema: "ruview.lidar.depth.v1"
)
}
func assigningSequence(_ sequence: UInt64) -> RuViewLiDARFrame {
RuViewLiDARFrame(
type: type,
intrinsics: intrinsics,
pose: pose,
depth: depth,
provenance: Provenance(
sensor: provenance.sensor,
source: provenance.source,
privacyClass: provenance.privacyClass,
sequence: sequence,
timestampNs: provenance.timestampNs,
schema: provenance.schema
)
)
}
private init(
type: String,
intrinsics: Intrinsics,
pose: Pose,
depth: Depth,
provenance: Provenance
) {
self.type = type
self.intrinsics = intrinsics
self.pose = pose
self.depth = depth
self.provenance = provenance
}
}
private extension simd_float4x4 {
var columnMajorArray: [Float] {
[
columns.0.x, columns.0.y, columns.0.z, columns.0.w,
columns.1.x, columns.1.y, columns.1.z, columns.1.w,
columns.2.x, columns.2.y, columns.2.z, columns.2.w,
columns.3.x, columns.3.y, columns.3.z, columns.3.w
]
}
}

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import SwiftUI
@main
struct RuViewLiDARApp: App {
var body: some Scene {
WindowGroup {
ContentView()
}
}
}

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import Foundation
actor WebSocketStreamer {
enum StreamError: Error {
case invalidURL
}
struct WirePacket: Codable {
struct Depth: Codable {
let width: Int
let height: Int
let encoding: String
let millimetersBase64: String
let confidenceBase64: String
}
let type: String
let intrinsics: RuViewLiDARFrame.Intrinsics
let pose: RuViewLiDARFrame.Pose
let depth: Depth
let provenance: RuViewLiDARFrame.Provenance
}
private var task: URLSessionWebSocketTask?
private let encoder = JSONEncoder()
private var lastSentNs: UInt64 = 0
func connect(to endpoint: String) throws {
guard let url = URL(string: endpoint),
url.scheme == "ws" || url.scheme == "wss" else {
throw StreamError.invalidURL
}
task?.cancel(with: .goingAway, reason: nil)
let socket = URLSession.shared.webSocketTask(with: url)
socket.resume()
task = socket
}
func disconnect() {
task?.cancel(with: .goingAway, reason: nil)
task = nil
}
func send(_ frame: RuViewLiDARFrame, maxFPS: UInt64 = 15, sampleStep: Int = 2) async throws {
guard let task else { return }
let timestamp = frame.provenance.timestampNs
let minDelta = 1_000_000_000 / max(1, maxFPS)
guard timestamp >= lastSentNs + minDelta else { return }
lastSentNs = timestamp
let packet = Self.makeWirePacket(frame, sampleStep: max(1, sampleStep))
let data = try encoder.encode(packet)
guard let string = String(data: data, encoding: .utf8) else { return }
try await task.send(.string(string))
}
static func makeWirePacket(_ frame: RuViewLiDARFrame, sampleStep: Int) -> WirePacket {
let step = max(1, sampleStep)
let sourceWidth = frame.depth.width
let sourceHeight = frame.depth.height
let width = (sourceWidth + step - 1) / step
let height = (sourceHeight + step - 1) / step
var millimeters = Data(capacity: width * height * 2)
var confidence = Data(capacity: width * height)
for y in stride(from: 0, to: sourceHeight, by: step) {
for x in stride(from: 0, to: sourceWidth, by: step) {
let index = y * sourceWidth + x
let meters = frame.depth.meters[index]
let mm = UInt16(clamping: Int((meters * 1000).rounded()))
var littleEndian = mm.littleEndian
withUnsafeBytes(of: &littleEndian) { millimeters.append(contentsOf: $0) }
confidence.append(frame.depth.confidence[index])
}
}
return WirePacket(
type: frame.type,
intrinsics: frame.intrinsics,
pose: frame.pose,
depth: WirePacket.Depth(
width: width,
height: height,
encoding: "u16le-mm+u8-confidence",
millimetersBase64: millimeters.base64EncodedString(),
confidenceBase64: confidence.base64EncodedString()
),
provenance: frame.provenance
)
}
}

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import { decodeLiDARPacket, depthToPointCloud } from './codec.mjs';
const canvas = document.querySelector('#view');
const ctx = canvas.getContext('2d');
const status = document.querySelector('#status');
const fpsEl = document.querySelector('#fps');
const pointsEl = document.querySelector('#points');
const seqEl = document.querySelector('#seq');
const latencyEl = document.querySelector('#latency');
const sensorEl = document.querySelector('#sensor');
let lastFrameAt = performance.now();
let yaw = 0.3;
let pitch = -0.15;
let scale = 120;
function connect() {
const token = new URLSearchParams(location.search).get('token');
if (!token) {
status.textContent = 'TOKEN REQUIRED';
status.dataset.state = 'warn';
return;
}
const protocol = location.protocol === 'https:' ? 'wss:' : 'ws:';
const socket = new WebSocket(`${protocol}//${location.host}/ws/lidar?token=${encodeURIComponent(token)}`);
socket.addEventListener('open', () => {
status.textContent = 'LIVE';
status.dataset.state = 'live';
});
socket.addEventListener('close', () => {
status.textContent = 'RECONNECTING';
status.dataset.state = 'warn';
setTimeout(connect, 1000);
});
socket.addEventListener('message', (event) => {
try {
const raw = JSON.parse(event.data);
const frame = decodeLiDARPacket(raw);
const points = depthToPointCloud(frame, 1);
render(points);
const now = performance.now();
const delta = now - lastFrameAt;
lastFrameAt = now;
fpsEl.textContent = delta > 0 ? (1000 / delta).toFixed(1) : '0.0';
pointsEl.textContent = points.length.toLocaleString();
seqEl.textContent = frame.provenance.sequence;
latencyEl.textContent = Math.max(0, Date.now() - Number(frame.provenance.timestampNs / 1_000_000)).toFixed(0);
sensorEl.textContent = frame.provenance.sensor;
} catch (error) {
console.error(error);
status.textContent = 'FRAME ERROR';
status.dataset.state = 'warn';
}
});
}
function resize() {
const dpr = Math.min(devicePixelRatio || 1, 2);
const rect = canvas.getBoundingClientRect();
canvas.width = Math.max(1, Math.floor(rect.width * dpr));
canvas.height = Math.max(1, Math.floor(rect.height * dpr));
ctx.setTransform(dpr, 0, 0, dpr, 0, 0);
}
function render(points) {
resize();
const w = canvas.clientWidth;
const h = canvas.clientHeight;
ctx.clearRect(0, 0, w, h);
ctx.fillStyle = '#091018';
ctx.fillRect(0, 0, w, h);
const cy = Math.cos(yaw);
const sy = Math.sin(yaw);
const cp = Math.cos(pitch);
const sp = Math.sin(pitch);
ctx.fillStyle = '#58e0d2';
for (let i = 0; i < points.length; i += 1) {
let [x, y, z] = points[i];
const rx = x * cy - z * sy;
const rz = x * sy + z * cy;
const ry = y * cp - rz * sp;
const rz2 = y * sp + rz * cp;
const perspective = 1 / Math.max(0.35, 1.8 - rz2 * 0.12);
const px = w / 2 + rx * scale * perspective;
const py = h / 2 + ry * scale * perspective;
if (px >= 0 && px < w && py >= 0 && py < h) ctx.fillRect(px, py, 1.4, 1.4);
}
}
canvas.addEventListener('pointermove', (event) => {
if (!event.buttons) return;
yaw += event.movementX * 0.006;
pitch += event.movementY * 0.006;
});
canvas.addEventListener('wheel', (event) => {
event.preventDefault();
scale = Math.max(40, Math.min(400, scale - event.deltaY * 0.2));
}, { passive: false });
connect();

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export function decodeLiDARPacket(packet) {
if (!packet || packet.type !== 'ruview.lidar.depth.v1') {
throw new Error('Unsupported LiDAR packet type');
}
const { depth } = packet;
if (!depth || depth.encoding !== 'u16le-mm+u8-confidence') {
throw new Error('Unsupported depth encoding');
}
assertPositiveInteger(depth.width, 'depth.width');
assertPositiveInteger(depth.height, 'depth.height');
assertIntrinsics(packet.intrinsics);
if (!packet.pose || !Array.isArray(packet.pose.matrix) || packet.pose.matrix.length !== 16
|| packet.pose.matrix.some((value) => !Number.isFinite(value))) {
throw new Error('Invalid camera pose');
}
const mmBytes = base64ToBytes(depth.millimetersBase64, 'millimetersBase64');
const confidence = base64ToBytes(depth.confidenceBase64, 'confidenceBase64');
const expectedPixels = depth.width * depth.height;
if (!Number.isSafeInteger(expectedPixels) || expectedPixels > 1_000_000) {
throw new Error('Depth dimensions exceed the supported pixel limit');
}
if (mmBytes.byteLength !== expectedPixels * 2) {
throw new Error(`Depth payload length mismatch: expected ${expectedPixels * 2}, got ${mmBytes.byteLength}`);
}
if (confidence.byteLength !== expectedPixels) {
throw new Error(`Confidence payload length mismatch: expected ${expectedPixels}, got ${confidence.byteLength}`);
}
const view = new DataView(mmBytes.buffer, mmBytes.byteOffset, mmBytes.byteLength);
const meters = new Float32Array(expectedPixels);
for (let i = 0; i < expectedPixels; i += 1) {
meters[i] = view.getUint16(i * 2, true) / 1000;
}
return {
...packet,
depth: {
width: depth.width,
height: depth.height,
meters,
confidence,
},
};
}
export function depthToPointCloud(frame, confidenceThreshold = 1) {
const { width, height, meters, confidence } = frame.depth;
const { fx, fy, cx, cy, imageWidth, imageHeight } = frame.intrinsics;
assertPositiveInteger(width, 'depth.width');
assertPositiveInteger(height, 'depth.height');
assertIntrinsics(frame.intrinsics);
if (meters.length !== width * height || confidence.length !== width * height) {
throw new Error('Decoded depth array length mismatch');
}
if (!Number.isFinite(confidenceThreshold) || confidenceThreshold < 0 || confidenceThreshold > 255) {
throw new Error('Invalid confidence threshold');
}
const sx = width / imageWidth;
const sy = height / imageHeight;
const scaledFx = fx * sx;
const scaledFy = fy * sy;
const scaledCx = cx * sx;
const scaledCy = cy * sy;
const points = [];
for (let v = 0; v < height; v += 1) {
for (let u = 0; u < width; u += 1) {
const index = v * width + u;
const z = meters[index];
if (!Number.isFinite(z) || z <= 0 || confidence[index] < confidenceThreshold) continue;
const x = ((u - scaledCx) / scaledFx) * z;
const y = ((v - scaledCy) / scaledFy) * z;
points.push([x, y === 0 ? 0 : -y, -z]);
}
}
return points;
}
function assertPositiveInteger(value, name) {
if (!Number.isSafeInteger(value) || value <= 0) {
throw new Error(`${name} must be a positive integer`);
}
}
function assertIntrinsics(intrinsics) {
if (!intrinsics
|| !Number.isFinite(intrinsics.fx) || intrinsics.fx <= 0
|| !Number.isFinite(intrinsics.fy) || intrinsics.fy <= 0
|| !Number.isFinite(intrinsics.cx)
|| !Number.isFinite(intrinsics.cy)) {
throw new Error('Invalid camera intrinsics');
}
assertPositiveInteger(intrinsics.imageWidth, 'intrinsics.imageWidth');
assertPositiveInteger(intrinsics.imageHeight, 'intrinsics.imageHeight');
}
function base64ToBytes(value, name) {
if (typeof value !== 'string' || value.length === 0 || value.length % 4 !== 0
|| !/^(?:[A-Za-z0-9+/]{4})*(?:[A-Za-z0-9+/]{2}==|[A-Za-z0-9+/]{3}=)?$/.test(value)) {
throw new Error(`${name} must be canonical base64`);
}
if (typeof Buffer !== 'undefined') {
return Uint8Array.from(Buffer.from(value, 'base64'));
}
const binary = atob(value);
const bytes = new Uint8Array(binary.length);
for (let i = 0; i < binary.length; i += 1) {
bytes[i] = binary.charCodeAt(i);
}
return bytes;
}

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import test from 'node:test';
import assert from 'node:assert/strict';
import { decodeLiDARPacket, depthToPointCloud } from './codec.mjs';
function b64(bytes) {
return Buffer.from(bytes).toString('base64');
}
test('decodes u16 millimeter depth and confidence', () => {
const packet = {
type: 'ruview.lidar.depth.v1',
intrinsics: { fx: 100, fy: 100, cx: 1, cy: 1, imageWidth: 2, imageHeight: 2 },
pose: { matrix: Array(16).fill(0) },
depth: {
width: 2,
height: 2,
encoding: 'u16le-mm+u8-confidence',
millimetersBase64: b64([0xe8,0x03,0xd0,0x07,0xb8,0x0b,0xa0,0x0f]),
confidenceBase64: b64([2,2,1,0]),
},
provenance: { sensor: 'test', source: 'live', privacyClass: 'geometry-only', sequence: 1, timestampNs: 1, schema: 'ruview.lidar.depth.v1' },
};
const frame = decodeLiDARPacket(packet);
assert.deepEqual(Array.from(frame.depth.meters), [1,2,3,4]);
assert.deepEqual(Array.from(frame.depth.confidence), [2,2,1,0]);
});
test('rejects malformed payload length', () => {
assert.throws(() => decodeLiDARPacket({
type: 'ruview.lidar.depth.v1',
intrinsics: { fx: 100, fy: 100, cx: 1, cy: 1, imageWidth: 2, imageHeight: 2 },
pose: { matrix: Array(16).fill(0) },
depth: { width: 2, height: 2, encoding: 'u16le-mm+u8-confidence', millimetersBase64: b64([1,2]), confidenceBase64: b64([1,1,1,1]) },
}), /length mismatch/);
});
test('rejects invalid dimensions, intrinsics, pose, and base64', () => {
const valid = {
type: 'ruview.lidar.depth.v1',
intrinsics: { fx: 100, fy: 100, cx: 0, cy: 0, imageWidth: 1, imageHeight: 1 },
pose: { matrix: Array(16).fill(0) },
depth: {
width: 1,
height: 1,
encoding: 'u16le-mm+u8-confidence',
millimetersBase64: b64([0xe8, 0x03]),
confidenceBase64: b64([2]),
},
};
assert.throws(() => decodeLiDARPacket({ ...valid, depth: { ...valid.depth, width: 0 } }), /positive integer/);
assert.throws(() => decodeLiDARPacket({ ...valid, intrinsics: { ...valid.intrinsics, fx: 0 } }), /intrinsics/);
assert.throws(() => decodeLiDARPacket({ ...valid, pose: { matrix: [1] } }), /pose/);
assert.throws(() => decodeLiDARPacket({
...valid,
depth: { ...valid.depth, millimetersBase64: '!!!!' },
}), /canonical base64/);
});
test('projects depth into a point cloud and honors confidence', () => {
const frame = {
intrinsics: { fx: 100, fy: 100, cx: 0, cy: 0, imageWidth: 2, imageHeight: 2 },
depth: { width: 2, height: 2, meters: Float32Array.from([1,1,1,1]), confidence: Uint8Array.from([2,0,2,0]) },
};
const points = depthToPointCloud(frame, 1);
assert.equal(points.length, 2);
assert.deepEqual(points[0], [0, 0, -1]);
});

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<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width,initial-scale=1,viewport-fit=cover" />
<title>RuView iPhone LiDAR</title>
<link rel="stylesheet" href="./styles.css" />
</head>
<body>
<main>
<header>
<div>
<p class="eyebrow">RUVIEW SENSOR BRIDGE</p>
<h1>iPhone LiDAR</h1>
</div>
<span id="status">CONNECTING</span>
</header>
<section class="metrics">
<div><strong id="fps">0.0</strong><span>FPS</span></div>
<div><strong id="points">0</strong><span>POINTS</span></div>
<div><strong id="seq">0</strong><span>SEQ</span></div>
<div><strong id="latency">0</strong><span>MS</span></div>
</section>
<canvas id="view"></canvas>
<footer>
<span>Geometry only</span>
<span>No RGB upload</span>
<span id="sensor">Waiting for sensor</span>
</footer>
</main>
<script type="module" src="./app.mjs"></script>
</body>
</html>

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{
"name": "@ruview/iphone-lidar-web",
"version": "0.1.0",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "@ruview/iphone-lidar-web",
"version": "0.1.0",
"dependencies": {
"ws": "^8.18.3"
},
"engines": {
"node": ">=20"
}
},
"node_modules/ws": {
"version": "8.21.3",
"resolved": "https://registry.npmjs.org/ws/-/ws-8.21.3.tgz",
"integrity": "sha512-201TZ/kPWxoPr/OKWjquZR1SWKXcvxdH+e1xrx89b3YbmzLMFCLfnaG1HFIgWzJOEWZ7MvpK++odZufgYR50Rw==",
"license": "MIT",
"engines": {
"node": ">=10.0.0"
},
"peerDependencies": {
"bufferutil": "^4.0.1",
"utf-8-validate": ">=5.0.2"
},
"peerDependenciesMeta": {
"bufferutil": {
"optional": true
},
"utf-8-validate": {
"optional": true
}
}
}
}
}

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{
"name": "@ruview/iphone-lidar-web",
"private": true,
"version": "0.1.0",
"type": "module",
"scripts": {
"start": "node relay.mjs",
"test": "node --test"
},
"engines": {
"node": ">=20"
},
"dependencies": {
"ws": "^8.18.3"
}
}

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import { randomBytes, timingSafeEqual } from 'node:crypto';
import http from 'node:http';
import { readFile } from 'node:fs/promises';
import { extname, join } from 'node:path';
import { fileURLToPath, pathToFileURL } from 'node:url';
import { WebSocket, WebSocketServer } from 'ws';
const root = fileURLToPath(new URL('.', import.meta.url));
const staticFiles = new Set(['index.html', 'app.mjs', 'codec.mjs', 'styles.css']);
const maxPayloadBytes = 2_000_000;
function constantTimeEqual(left, right) {
const leftBytes = Buffer.from(left, 'utf8');
const rightBytes = Buffer.from(right, 'utf8');
return leftBytes.length === rightBytes.length && timingSafeEqual(leftBytes, rightBytes);
}
function rejectUpgrade(socket, status, message) {
const body = `${message}\n`;
socket.end(
`HTTP/1.1 ${status}\r\nConnection: close\r\nContent-Type: text/plain; charset=utf-8\r\nContent-Length: ${Buffer.byteLength(body)}\r\n\r\n${body}`,
);
}
export function createLiDARRelay({ token, rootDirectory = root } = {}) {
const accessToken = token || randomBytes(24).toString('hex');
const clients = new Set();
const server = http.createServer(async (req, res) => {
if (req.method !== 'GET' && req.method !== 'HEAD') {
res.writeHead(405, { allow: 'GET, HEAD' }).end();
return;
}
let pathname;
try {
pathname = decodeURIComponent(new URL(req.url || '/', 'http://localhost').pathname);
} catch {
res.writeHead(400).end('bad path');
return;
}
const filename = pathname === '/' ? 'index.html' : pathname.slice(1);
if (!staticFiles.has(filename)) {
res.writeHead(404).end('not found');
return;
}
try {
const data = await readFile(join(rootDirectory, filename));
const contentType = {
'.html': 'text/html; charset=utf-8',
'.mjs': 'text/javascript; charset=utf-8',
'.css': 'text/css; charset=utf-8',
}[extname(filename)] || 'application/octet-stream';
res.writeHead(200, {
'content-type': contentType,
'cache-control': 'no-store',
'content-security-policy': "default-src 'self'; connect-src 'self' ws: wss:; img-src 'self'; style-src 'self'; base-uri 'none'; frame-ancestors 'none'",
'referrer-policy': 'no-referrer',
'x-content-type-options': 'nosniff',
});
if (req.method === 'HEAD') res.end();
else res.end(data);
} catch {
res.writeHead(404).end('not found');
}
});
const wss = new WebSocketServer({ noServer: true, maxPayload: maxPayloadBytes });
server.on('upgrade', (req, socket, head) => {
let url;
try {
url = new URL(req.url || '/', 'http://localhost');
} catch {
rejectUpgrade(socket, '400 Bad Request', 'bad websocket URL');
return;
}
if (url.pathname !== '/ws/lidar') {
rejectUpgrade(socket, '404 Not Found', 'not found');
return;
}
const suppliedToken = url.searchParams.get('token') || '';
if (!constantTimeEqual(suppliedToken, accessToken)) {
rejectUpgrade(socket, '401 Unauthorized', 'valid LiDAR relay token required');
return;
}
wss.handleUpgrade(req, socket, head, (websocket) => {
wss.emit('connection', websocket, req);
});
});
wss.on('connection', (socket) => {
clients.add(socket);
socket.on('close', () => clients.delete(socket));
socket.on('error', () => socket.terminate());
socket.on('message', (data, isBinary) => {
if (isBinary) return;
let packet;
try {
packet = JSON.parse(data.toString());
} catch {
return;
}
if (packet?.type !== 'ruview.lidar.depth.v1') return;
for (const peer of clients) {
if (peer !== socket && peer.readyState === WebSocket.OPEN) {
peer.send(data.toString());
}
}
});
});
return {
accessToken,
server,
async listen(port = 0, host = '127.0.0.1') {
await new Promise((resolve, reject) => {
server.once('error', reject);
server.listen(port, host, () => {
server.off('error', reject);
resolve();
});
});
return server.address();
},
async close() {
for (const peer of clients) peer.terminate();
await new Promise((resolve) => wss.close(resolve));
if (server.listening) {
await new Promise((resolve, reject) => {
server.close((error) => (error ? reject(error) : resolve()));
});
}
},
};
}
function configuredPort(value) {
const parsed = Number(value);
if (!Number.isSafeInteger(parsed) || parsed < 1 || parsed > 65_535) {
throw new Error(`PORT must be an integer from 1 to 65535; received ${value}`);
}
return parsed;
}
const directInvocation = process.argv[1]
&& pathToFileURL(process.argv[1]).href === import.meta.url;
if (directInvocation) {
const port = configuredPort(process.env.PORT || '8787');
const host = process.env.HOST || '0.0.0.0';
const relay = createLiDARRelay({ token: process.env.RUVIEW_LIDAR_TOKEN });
await relay.listen(port, host);
const encodedToken = encodeURIComponent(relay.accessToken);
console.log(`RuView iPhone LiDAR relay listening on ${host}:${port}`);
console.log(`Browser: http://<host>:${port}/?token=${encodedToken}`);
console.log(`Native endpoint: ws://<host>:${port}/ws/lidar?token=${encodedToken}`);
}

View File

@@ -0,0 +1,73 @@
import assert from 'node:assert/strict';
import http from 'node:http';
import test from 'node:test';
import { WebSocket } from 'ws';
import { createLiDARRelay } from './relay.mjs';
function connect(url) {
return new Promise((resolve, reject) => {
const socket = new WebSocket(url);
socket.once('open', () => resolve(socket));
socket.once('error', reject);
});
}
function request(url) {
return new Promise((resolve, reject) => {
http.get(url, (response) => {
response.resume();
response.once('end', () => resolve(response));
}).once('error', reject);
});
}
test('relay requires a token, limits static files, and forwards LiDAR frames', async (t) => {
const token = 'test-token-for-relay';
const relay = createLiDARRelay({ token });
const address = await relay.listen(0, '127.0.0.1');
const httpBase = `http://127.0.0.1:${address.port}`;
const wsBase = `ws://127.0.0.1:${address.port}/ws/lidar`;
const sockets = [];
t.after(async () => {
for (const socket of sockets) socket.terminate();
await relay.close();
});
const indexResponse = await request(`${httpBase}/?token=${token}`);
assert.equal(indexResponse.statusCode, 200);
assert.match(indexResponse.headers['content-security-policy'], /frame-ancestors 'none'/);
const sourceResponse = await request(`${httpBase}/relay.mjs`);
assert.equal(sourceResponse.statusCode, 404);
await new Promise((resolve, reject) => {
const unauthorized = new WebSocket(wsBase);
unauthorized.once('unexpected-response', (_request, response) => {
assert.equal(response.statusCode, 401);
response.resume();
resolve();
});
unauthorized.once('open', () => reject(new Error('unauthorized websocket opened')));
unauthorized.once('error', () => {});
});
const sender = await connect(`${wsBase}?token=${encodeURIComponent(token)}`);
const receiver = await connect(`${wsBase}?token=${encodeURIComponent(token)}`);
sockets.push(sender, receiver);
const received = new Promise((resolve, reject) => {
const timer = setTimeout(() => reject(new Error('timed out waiting for relayed frame')), 2_000);
receiver.once('message', (data, isBinary) => {
clearTimeout(timer);
resolve({ data, isBinary });
});
});
const frame = { type: 'ruview.lidar.depth.v1', provenance: { sequence: 7 } };
sender.send(JSON.stringify(frame));
const message = await received;
assert.equal(message.isBinary, false);
assert.deepEqual(JSON.parse(message.data.toString()), frame);
});

View File

@@ -0,0 +1 @@
*{box-sizing:border-box}body{margin:0;background:#05080d;color:#e8f1f5;font-family:ui-monospace,SFMono-Regular,Menlo,monospace}main{min-height:100vh;padding:18px;display:grid;grid-template-rows:auto auto 1fr auto;gap:14px}header{display:flex;align-items:end;justify-content:space-between}h1{margin:0;font-size:clamp(28px,6vw,54px)}.eyebrow{margin:0 0 6px;color:#58e0d2;font-size:11px;letter-spacing:.16em}#status{border:1px solid #2a3946;border-radius:999px;padding:7px 11px;font-size:11px}#status[data-state=live]{color:#58e0d2;border-color:#58e0d2}.metrics{display:grid;grid-template-columns:repeat(4,1fr);gap:8px}.metrics div{background:#0b1219;border:1px solid #17222d;border-radius:10px;padding:10px}.metrics strong{display:block;font-size:18px}.metrics span,footer{font-size:10px;color:#8aa0af}canvas{width:100%;height:100%;min-height:55vh;border-radius:14px;border:1px solid #17222d;background:#091018;touch-action:none}footer{display:flex;gap:16px;flex-wrap:wrap}@media(max-width:640px){.metrics{grid-template-columns:repeat(2,1fr)}canvas{min-height:58vh}}

View File

@@ -1,13 +1,9 @@
# cargo-audit configuration — v2 workspace
# Managed by security audit (fix/security-audit-rustsec-clippy branch).
#
# This file suppresses advisories in two categories:
# A) CVE-bearing advisories in TRANSITIVE deps we cannot upgrade directly
# because the parent published crate (ruvector-core 2.2.0) has not yet
# published a version with the fix. These are tracked as issues.
# B) UNMAINTAINED-only advisories (no CVE) flowing through dependencies
# that are purely transitive / build-time and have no user-facing attack
# surface in this workspace.
# This file suppresses UNMAINTAINED-only advisories (no CVE) flowing through
# dependencies that are purely transitive / build-time and have no
# user-facing attack surface in this workspace.
# Each entry documents the root cause and the mitigation path.
[advisories]
@@ -24,26 +20,6 @@
# Mitigation: Accept transitively until Tauri v2 drops GTK3 or a workspace
# override path becomes available.
ignore = [
# -----------------------------------------------------------------------
# CATEGORY A — transitive CVEs from ruvector-core 2.2.0 → reqwest 0.11
# ruvector-core 2.2.0 (latest on crates.io) depends on reqwest 0.11.27,
# which pulls in rustls 0.21 / rustls-webpki 0.101.7. We cannot upgrade
# this without a new ruvector-core release. Tracked in issue #812.
# The workspace's own TLS stack uses rustls-webpki 0.103.13 (patched);
# the vulnerable 0.101.7 instance is not reachable from our TLS code.
"RUSTSEC-2026-0098", # rustls-webpki 0.101.7: URI name constraint bypass
"RUSTSEC-2026-0099", # rustls-webpki 0.101.7: wildcard name constraint bypass
"RUSTSEC-2026-0104", # rustls-webpki 0.101.7: reachable panic in CRL parsing
# quinn-proto 0.11.13 is also pulled through midstreamer-quic 0.3 (now
# upgraded). The remaining 0.11.13 instance comes from the same
# ruvector-core transitive chain. Tracked in issue #812.
"RUSTSEC-2026-0037", # quinn-proto 0.11.13: DoS in Quinn endpoints
# CRL Distribution Point matching bug — same ruvector-core / reqwest 0.11
# transitive chain; rustls-webpki 0.101.7 also affected.
"RUSTSEC-2026-0049", # rustls-webpki <0.103.10: CRL authority matching
# -----------------------------------------------------------------------
# CATEGORY B — unmaintained / no CVE
"RUSTSEC-2024-0411", # gdkwayland-sys: unmaintained
"RUSTSEC-2024-0412", # gdk: unmaintained
"RUSTSEC-2024-0413", # atk: unmaintained

999
v2/Cargo.lock generated

File diff suppressed because it is too large Load Diff

View File

@@ -255,7 +255,7 @@ midstreamer-attractor = "0.2"
# ruvector integration (published on crates.io)
# Vendored at origin/main (a083bd77f) in vendor/ruvector; using crates.io versions
# until published. Bumps per ADR-152 §2.6 (2026-06-10 vendor sync survey).
ruvector-core = "2.2.0"
ruvector-core = "2.3.0"
ruvector-mincut = "2.0.6"
ruvector-attn-mincut = "2.0.4"
ruvector-temporal-tensor = "2.0.6"

View File

@@ -31,10 +31,16 @@ homecore = { path = "../homecore", version = "0.1.0-alpha.0" }
# Async runtime
tokio = { version = "1", features = ["sync", "rt", "rt-multi-thread", "time", "macros"] }
# SQLite via sqlx — only the lite feature set; no postgres, no tls
sqlx = { version = "0.8.1", default-features = false, features = [
"runtime-tokio-native-tls",
"sqlite",
# SQLite-only SQLx crates, pinned in lockstep because their direct APIs are
# semver-exempt. Depending on the umbrella `sqlx` package also resolves its
# unused MySQL backend (and vulnerable `rsa`) into Cargo.lock.
sqlx-core = { version = "=0.8.6", default-features = false, features = [
"_rt-tokio",
"chrono",
"uuid",
] }
sqlx-sqlite = { version = "=0.8.6", default-features = false, features = [
"bundled",
"chrono",
"uuid",
] }

View File

@@ -26,6 +26,19 @@ use homecore::StateMachine;
use crate::dedup::fnv64a_hash;
use crate::schema::ALL_DDL;
// Preserve the narrow `sqlx::*` call surface used in this module while
// depending only on SQLx core + SQLite. The umbrella crate resolves unused
// database backends into Cargo.lock, including MySQL's vulnerable RSA stack.
mod sqlx {
pub use sqlx_core::error::Error;
pub use sqlx_core::query::query;
pub use sqlx_core::query_as::query_as;
pub mod sqlite {
pub use sqlx_sqlite::{SqliteConnectOptions, SqlitePool, SqlitePoolOptions};
}
}
type SearchStateRecord = (
i64,
String,

View File

@@ -50,7 +50,7 @@ tower-http = { version = "0.6", features = ["fs", "trace", "cors"] }
# requires every crate that pulls reqwest to align on rustls-only (tracked in
# CHANGELOG / ADR-131 security note).
reqwest = { version = "0.12", default-features = false, features = ["json", "rustls-tls"] }
serde = { version = "1", features = ["derive"] }
serde = { version = "1", features = ["derive", "rc"] }
serde_yaml = "0.9"
# Concurrent fan-out of per-bank RoomState fetches in the gateway (§11 perf).
futures = "0.3"

View File

@@ -39,7 +39,7 @@ serde = { workspace = true, features = ["derive"], optional = true }
serde_json = { workspace = true, optional = true }
# MQTT publisher backend (optional). Matches the `rumqttc` choice already in
# `wifi-densepose-sensing-server` so both crates share TLS / version posture.
rumqttc = { version = "0.24", default-features = false, features = ["use-rustls"], optional = true }
rumqttc = { package = "rumqttc-v4-next", version = "0.34", default-features = false, features = ["use-rustls-ring"], optional = true }
wifi-veil = { workspace = true, optional = true }
[dev-dependencies]

View File

@@ -31,7 +31,7 @@ use crate::PrivacyClass;
/// };
/// use rumqttc::MqttOptions;
///
/// let opts = MqttOptions::new("seed-01", "broker.local", 1883);
/// let opts = MqttOptions::new("seed-01", ("broker.local", 1883));
/// let (retained_pub, _conn) = RumqttPublisher::connect(opts.clone(), 64);
/// let mut retained_pub = retained_pub.with_retain(true);
/// publish_discovery(&mut retained_pub, "seed-01", PrivacyClass::Anonymous)?;

View File

@@ -13,7 +13,7 @@
//! use wifi_densepose_bfld::{publish_event, RumqttPublisher};
//! use rumqttc::MqttOptions;
//!
//! let opts = MqttOptions::new("seed-01", "broker.local", 1883);
//! let opts = MqttOptions::new("seed-01", ("broker.local", 1883));
//! let (mut publisher, mut connection) = RumqttPublisher::connect(opts, 100);
//! thread::spawn(move || for _ in connection.iter() { /* drain */ });
//! // ... build BfldEvent ...
@@ -22,7 +22,7 @@
#![cfg(feature = "mqtt")]
use rumqttc::{Client, Connection, LastWill, MqttOptions, QoS};
use rumqttc::{Client, Connection, LastWill, MqttOptions, PublishOptions, QoS};
use crate::availability::{availability_topic, PAYLOAD_NOT_AVAILABLE};
use crate::mqtt_topics::{Publish, TopicMessage};
@@ -60,7 +60,7 @@ impl RumqttPublisher {
/// shown in the module-level doc example).
#[must_use]
pub fn connect(opts: MqttOptions, capacity: usize) -> (Self, Connection) {
let (client, connection) = Client::new(opts, capacity);
let (client, connection) = Client::builder(opts).capacity(capacity).build();
(Self::new(client, QoS::AtLeastOnce), connection)
}
@@ -87,7 +87,7 @@ impl RumqttPublisher {
/// opt in to the LWT without using `connect_with_lwt`.
#[must_use]
pub fn with_lwt(mut opts: MqttOptions, node_id: &str) -> MqttOptions {
// rumqttc 0.24 LastWill::new takes (topic, message, qos, retain).
// LastWill::new takes (topic, message, qos, retain).
// retain = true so HA sees "offline" on next start even if the session
// dropped while HA was down.
let will = LastWill::new(
@@ -105,6 +105,10 @@ impl Publish for RumqttPublisher {
fn publish(&mut self, msg: &TopicMessage) -> Result<(), Self::Error> {
self.client
.publish(&msg.topic, self.qos, self.retain, msg.payload.as_bytes())
.publish(
&msg.topic,
msg.payload.as_bytes(),
PublishOptions::new(self.qos).retain(self.retain),
)
}
}

View File

@@ -23,9 +23,7 @@ use std::thread;
use std::time::{Duration, Instant, SystemTime, UNIX_EPOCH};
use rumqttc::{Client, Event, Incoming, MqttOptions, Packet, QoS};
use wifi_densepose_bfld::{
publish_event, BfldEvent, PrivacyClass, RumqttPublisher,
};
use wifi_densepose_bfld::{publish_event, BfldEvent, PrivacyClass, RumqttPublisher};
const SUBSCRIBE_TIMEOUT: Duration = Duration::from_secs(5);
const RECEIVE_TIMEOUT: Duration = Duration::from_secs(10);
@@ -69,9 +67,9 @@ fn spawn_subscriber(
port: u16,
topic_filter: &str,
) -> (Receiver<(String, String)>, Receiver<()>) {
let mut opts = MqttOptions::new(unique_client_id("bfld-sub"), host, port);
opts.set_keep_alive(Duration::from_secs(5));
let (client, mut connection) = Client::new(opts, 64);
let mut opts = MqttOptions::new(unique_client_id("bfld-sub"), (host, port));
opts.set_keep_alive(5);
let (client, mut connection) = Client::builder(opts).capacity(64).build();
client
.subscribe(topic_filter, QoS::AtLeastOnce)
.expect("subscribe enqueue");
@@ -79,13 +77,18 @@ fn spawn_subscriber(
let (incoming_tx, incoming_rx) = channel();
let (suback_tx, suback_rx) = channel();
thread::spawn(move || {
// rumqttc-v4-next stops the connection once every request sender is
// dropped. Keep the subscriber client alive for as long as its pump
// thread runs; otherwise the broker sees a clean disconnect directly
// after SUBACK and no subsequent publications can be delivered.
let _client_guard = client;
for notification in connection.iter() {
match notification {
Ok(Event::Incoming(Packet::SubAck(_))) => {
let _ = suback_tx.send(());
}
Ok(Event::Incoming(Incoming::Publish(p))) => {
let topic = p.topic.clone();
let topic = String::from_utf8_lossy(&p.topic).to_string();
let payload = String::from_utf8_lossy(&p.payload).to_string();
if incoming_tx.send((topic, payload)).is_err() {
break;
@@ -141,8 +144,8 @@ fn live_broker_anonymous_event_roundtrips_all_six_topics() {
// Publisher with its own connection. Spawn a thread iterating the
// Connection so publishes actually reach the broker.
let mut opts = MqttOptions::new(unique_client_id("bfld-pub"), &host, port);
opts.set_keep_alive(Duration::from_secs(5));
let mut opts = MqttOptions::new(unique_client_id("bfld-pub"), (host.as_str(), port));
opts.set_keep_alive(5);
let (mut publisher, mut pub_connection) = RumqttPublisher::connect(opts, 64);
thread::spawn(move || {
for _ in pub_connection.iter() { /* drain protocol events */ }
@@ -197,8 +200,8 @@ fn live_broker_restricted_event_omits_identity_risk() {
.recv_timeout(SUBSCRIBE_TIMEOUT)
.expect("SubAck within 5s");
let mut opts = MqttOptions::new(unique_client_id("bfld-pub-r"), &host, port);
opts.set_keep_alive(Duration::from_secs(5));
let mut opts = MqttOptions::new(unique_client_id("bfld-pub-r"), (host.as_str(), port));
opts.set_keep_alive(5);
let (mut publisher, mut pub_connection) = RumqttPublisher::connect(opts, 64);
thread::spawn(move || for _ in pub_connection.iter() {});
thread::sleep(Duration::from_millis(200));

View File

@@ -9,7 +9,7 @@ use wifi_densepose_bfld::{
};
fn unreachable_opts(client_id: &str) -> MqttOptions {
MqttOptions::new(client_id, "127.0.0.1", 1)
MqttOptions::new(client_id, ("127.0.0.1", 1))
}
#[test]
@@ -89,7 +89,7 @@ fn caller_built_options_can_opt_in_via_with_lwt_then_pass_to_connect() {
// Operators with custom MqttOptions (e.g., TLS, credentials) build their
// own opts, then call with_lwt before passing to RumqttPublisher::connect.
let mut opts = unreachable_opts("bfld-lwt-6");
opts.set_keep_alive(std::time::Duration::from_secs(30));
opts.set_keep_alive(30);
let opts = with_lwt(opts, "seed-01");
let (_publisher, _connection) = RumqttPublisher::connect(opts, 16);
}

View File

@@ -12,7 +12,7 @@ use wifi_densepose_bfld::{publish_event, BfldEvent, PrivacyClass, Publish, Rumqt
fn unreachable_opts() -> MqttOptions {
// Port 1 is reserved (RFC 1700) and the loopback address will refuse
// immediately — perfect for a construction smoke test that must not block.
MqttOptions::new("bfld-smoke-iter23", "127.0.0.1", 1)
MqttOptions::new("bfld-smoke-iter23", ("127.0.0.1", 1))
}
fn sample_event() -> BfldEvent {

View File

@@ -19,6 +19,10 @@ rufield-core = { version = "0.1.0", path = "../../../vendor/rufield/crates/rufie
rufield-provenance = { version = "0.1.0", path = "../../../vendor/rufield/crates/rufield-provenance" }
rufield-privacy = { version = "0.1.0", path = "../../../vendor/rufield/crates/rufield-privacy" }
rufield-fusion = { version = "0.1.0", path = "../../../vendor/rufield/crates/rufield-fusion" }
# ADR-262 P4 second modality: UltrasonicReplayAdapter parses, validates and
# signs BatVu range profiles upstream, so RuView only has to decide what it is
# willing to put on a wire. Same pure-Rust constraint as the four above.
rufield-adapters = { version = "0.1.0", path = "../../../vendor/rufield/crates/rufield-adapters" }
serde = { workspace = true }
serde_json = { workspace = true }

View File

@@ -145,6 +145,21 @@ pub fn snapshot_to_field_event(snap: &SensingSnapshot, signer: &Signer) -> Field
features: build_features(snap, range_m),
labels: build_labels(snap),
privacy_class: class,
// ── fields added upstream since the previous submodule pin ─────────
//
// Each empty for its own reason rather than because a default was
// convenient. `track_id`: this bridge emits per-cycle snapshots, not
// tracks, and a stable per-person identifier is exactly what §3.3
// warns about. `attributes`: nothing `features` and `labels` do not
// already carry, and an empty map is omitted from the wire.
// `identity_evidence` / `channel_sounding_provenance`: both are
// structurally BLE-only — `validate_evidence_at` rejects either on any
// other modality — so for `wifi_csi` they are not unset, they are
// unrepresentable.
track_id: None,
attributes: Default::default(),
identity_evidence: None,
channel_sounding_provenance: None,
};
// ── 3. Provenance (real sha256 over the tensor bytes) ───────────────────
@@ -166,6 +181,15 @@ pub fn snapshot_to_field_event(snap: &SensingSnapshot, signer: &Signer) -> Field
vendor: "esp32".to_string(),
device_id: snap.node_id.clone(),
placement: "unknown".to_string(),
// Optional sensor pose, added upstream. Left unset on purpose: a CSI
// link has no boresight and no surveyed position here, and §6 is
// explicit that this surface makes no validated room-coordinate claim
// (`field_localize`). A placeholder pose would be inventing exactly
// that claim. The ultrasonic path DOES set these, because a handheld
// scanner genuinely knows where it was pointing.
coordinate_frame: None,
position_m: None,
orientation_xyzw: None,
clock_domain: "local".to_string(),
};

View File

@@ -71,12 +71,14 @@
pub mod bridge;
pub mod privacy;
pub mod snapshot;
pub mod ultrasonic;
pub use bridge::{snapshot_egress_class, snapshot_to_field_event};
pub use privacy::{apply_demotion_floor, egress_class, map_privacy};
pub use snapshot::{
RuViewPrivacyClass, SensingClass, SensingFeatures, SensingSnapshot, SignalField,
};
pub use ultrasonic::{ScanError, ScanSource, UltrasonicScan, ULTRASONIC_EGRESS_CLASS};
// Re-export the rufield surface a bridge consumer needs, so callers depend on
// one crate.

View File

@@ -0,0 +1,233 @@
//! ADR-262 **P4, second modality**: ultrasonic range profiles on the field
//! surface.
//!
//! Until now RuView's `/api/field` and `/ws/field` have carried exactly one
//! modality — WiFi CSI, through [`crate::bridge`]. ADR-262 §4 lists multi-
//! modality as P4 and leaves the choice of the second one open (§8 question 5
//! asks whether it should be `rvcsi`, "making RuField the convergence point for
//! both vendored sensing runtimes").
//!
//! This is a different answer to that question, and the reason is that it costs
//! almost nothing: `rufield-adapters` now ships
//! [`UltrasonicReplayAdapter`](rufield_adapters::UltrasonicReplayAdapter), the
//! first adapter for `Modality::Ultrasonic` — registry code 7, which had sat in
//! the §8 registry since v0.1 with nothing implementing it. It parses, validates
//! and **signs** BatVu recordings upstream. RuView does not have to build any of
//! that; it has to decide what it is willing to put on a wire.
//!
//! # What BatVu is, in one paragraph
//!
//! [BatVu](https://github.com/ruvnet/batvu) is a handheld sonar that runs in a
//! phone browser: a 17.520.5 kHz chirp out of the speaker, a matched filter
//! over the microphone, and a **range profile** — echo amplitude against
//! distance along one beam. One microphone, so it measures range and infers
//! bearing only from where the operator was pointing. That asymmetry is why the
//! beam is carried as sensor *pose* rather than as an angle axis.
//!
//! # Why this module exists at all, given the adapter does the work
//!
//! Because RuView's egress rule is **stricter** than RuField's default guard,
//! and the difference has to be structural rather than a runtime refusal.
//!
//! The adapter offers two output modes. [`UltrasonicOutput::RangeProfile`] is
//! the full per-bin frame, classified `P0`, which
//! [`network_egress_allowed`](crate::network_egress_allowed) holds edge-local —
//! correctly, but *silently*, as a dropped event at the end of a pipeline that
//! did all the parsing and signing first.
//! [`UltrasonicOutput::CoarseProfile`] is a 32-bin max-pooled reduction,
//! classified `P1`, which is egress-safe.
//!
//! So this module does not offer the choice. It configures the adapter for the
//! coarse mode and says why, because a consumer cannot un-coarsen a coarse
//! profile and a policy expressed in the *shape of the data* cannot be
//! misconfigured later. The egress gate still runs — belt and braces, and it is
//! asserted by a test — but by then there is nothing left for it to catch.
//!
//! # Honesty (ADR-262 §0 / §6)
//!
//! Same posture as P1, plus one more caveat that is BatVu's rather than ours:
//!
//! 1. **Replay, not live.** A file, not a streaming phone.
//! 2. **Every current BatVu recording is its own simulator's output**, so the
//! events carry `synthetic: true` and are fusable only under
//! [`TrustPolicy::simulation`](rufield_provenance::TrustPolicy::simulation).
//! `captured_replay()` and `production()` reject them outright, as they
//! should. When a real device recording exists it declares
//! `device_capture` and this module refuses it unless the caller has asked
//! for that source explicitly — a recording cannot talk its way up a trust
//! tier by relabelling itself.
//! 3. **No accuracy is claimed.** The detections are CFAR outputs at a
//! documented false-alarm rate. That is an operating point, not validated
//! accuracy against surveyed ground truth.
//! 4. **Nothing here says a person is present.** The adapter deliberately
//! declines to populate the `presence` feature that would light up the
//! shipped `person_present` rule: one transducer pair cannot distinguish a
//! person from a coat over the back of a chair. The visible consequence is
//! that ultrasonic events currently produce no fused inferences at all, and
//! `ultrasonic_gates.rs` asserts that rather than papering over it.
//!
//! # What this does NOT do
//!
//! It does not touch the running server. P1 shipped as a library before P3
//! wired it in, and this follows the same staging: a tested translation with
//! its own gates, reviewable on its own, with the surface change as a separate
//! change once the shape is agreed. [`UltrasonicScan::egress_events`] returns
//! exactly what `FieldSurface::emit` would need to broadcast.
use rufield_adapters::{
UltrasonicConfig, UltrasonicOutput, UltrasonicReplayAdapter, UltrasonicSource,
};
use rufield_core::{FieldEvent, PrivacyClass};
use crate::network_egress_allowed;
/// Which recordings a deployment is willing to accept.
///
/// Mirrors [`UltrasonicSource`] rather than re-exporting it, so a caller does
/// not have to depend on `rufield-adapters` to make the choice — the bridge
/// stays the single coupling point (ADR-262 §5.4).
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum ScanSource {
/// Rendered by BatVu's acoustic simulator. Events are `synthetic: true`.
/// The safe default: it cannot be mistaken for a measurement.
Simulated,
/// Captured from a real phone microphone. Events are `synthetic: false`
/// and are eligible for captured-replay trust once the sensor key is
/// enrolled.
DeviceCapture,
}
impl From<ScanSource> for UltrasonicSource {
fn from(s: ScanSource) -> Self {
match s {
ScanSource::Simulated => UltrasonicSource::Simulated,
ScanSource::DeviceCapture => UltrasonicSource::DeviceCapture,
}
}
}
/// Errors from loading a BatVu recording.
#[derive(Debug, Clone, PartialEq)]
pub enum ScanError {
/// The recording failed the adapter's parser. Carries its message, which
/// names the offending line.
Parse(String),
/// Calibration could not be established.
Calibrate(String),
}
impl std::fmt::Display for ScanError {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
match self {
ScanError::Parse(m) => write!(f, "ultrasonic recording rejected: {m}"),
ScanError::Calibrate(m) => write!(f, "ultrasonic calibration failed: {m}"),
}
}
}
impl std::error::Error for ScanError {}
/// A loaded BatVu scan, ready to put on the field surface.
#[derive(Debug)]
pub struct UltrasonicScan {
adapter: UltrasonicReplayAdapter,
calibration_id: String,
}
impl UltrasonicScan {
/// Load a `.ultrasonic.jsonl` recording.
///
/// `zone_id` is the room the scan was taken in and lands on every
/// observation. `accept` declares which source the deployment will take; a
/// recording declaring anything else is **refused**, in both directions, so
/// neither is a silent reinterpretation.
///
/// Calibration runs here rather than being optional. The receipt id ends up
/// on every tensor, so an event that skipped it would be one nobody could
/// later ask "under what calibration was this measured".
pub fn load(text: &str, zone_id: &str, accept: ScanSource) -> Result<Self, ScanError> {
let config = UltrasonicConfig {
accept: accept.into(),
zone_id: zone_id.to_string(),
placement: "handheld".to_string(),
// Not a caller's choice. See the module docs: the raw per-bin frame
// is P0 and would be dropped by the egress gate after all the work
// of parsing and signing it. Coarsening at the source makes the
// policy a property of the data instead of a property of a check
// somebody could later reorder.
output: UltrasonicOutput::CoarseProfile,
};
let mut adapter = UltrasonicReplayAdapter::from_jsonl_with(text, config)
.map_err(|e| ScanError::Parse(e.to_string()))?;
let receipt = adapter
.calibrate(zone_id)
.map_err(|e| ScanError::Calibrate(e.to_string()))?;
Ok(UltrasonicScan {
adapter,
calibration_id: receipt.calibration_id,
})
}
/// Pings in the recording.
#[must_use]
pub fn ping_count(&self) -> usize {
self.adapter.ping_count()
}
/// The sensor identity the whole recording belongs to.
///
/// This is the key RuField's replay watermark and trust registry are both
/// keyed on, so it has to be stable across scans — the adapter refuses a
/// recording whose device changes midway.
#[must_use]
pub fn device_id(&self) -> &str {
self.adapter.device_id()
}
/// The calibration receipt every tensor in this scan cites.
#[must_use]
pub fn calibration_id(&self) -> &str {
&self.calibration_id
}
/// Every event in the recording, signed and validated by the adapter.
///
/// Includes events that the egress gate would refuse. Use this for an
/// edge-local consumer; use [`egress_events`](Self::egress_events) for
/// anything that reaches a network.
pub fn events(&mut self) -> Result<Vec<FieldEvent>, ScanError> {
self.adapter
.collect_events()
.map_err(|e| ScanError::Parse(e.to_string()))
}
/// Only the events RuView will put on the wire.
///
/// Runs the same [`network_egress_allowed`] gate the CSI path runs, with
/// `identity_bound: false` — an ultrasonic scan has no identity to bind, and
/// hard-coding it rather than plumbing a flag means there is no argument a
/// caller can pass that turns the P4/P5 consent exception on. There is no
/// consent story for a room scan.
///
/// In the coarse mode configured by [`load`](Self::load) this should drop
/// nothing, and `coarse_scan_passes_the_egress_gate_intact` asserts it. The
/// gate stays because a policy that is only enforced where it never fires
/// is a policy nobody notices removing.
pub fn egress_events(&mut self) -> Result<Vec<FieldEvent>, ScanError> {
Ok(self
.events()?
.into_iter()
.filter(|e| network_egress_allowed(e.observation.privacy_class, false))
.filter(|e| network_egress_allowed(e.tensor.privacy_class, false))
.collect())
}
}
/// The privacy class every event from [`UltrasonicScan`] carries.
///
/// `P1` — a derived non-identity feature. Stated as a constant so a test can
/// pin it: if the adapter's default output mode ever changes upstream, that is
/// a submodule bump which silently moves data from edge-local to network-eligible
/// or back, and it should fail a build here rather than change behaviour in a
/// deployment.
pub const ULTRASONIC_EGRESS_CLASS: PrivacyClass = PrivacyClass::P1;

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//! ADR-262 P4 gates for the second modality.
//!
//! Same shape as `p1_gates.rs`: round-trip, fusability, privacy-safety,
//! determinism. Not accuracy — nothing here claims an ultrasonic scan is
//! *right*, only that it is well-formed, signed, correctly classified, and that
//! the things it must refuse to do, it refuses.
//!
//! The fixture is not hand-written. `batvu_living_room.ultrasonic.jsonl` is
//! produced by BatVu's own `npm run artifacts` — a 72-ping simulated sweep,
//! written by its TypeScript emitter — and copied here verbatim. The same file
//! is a test fixture in `ruvnet/rufield`, so a schema drift between BatVu's
//! emitter and RuField's parser fails a build in one of three repositories
//! rather than an ingest in a deployment.
use rufield_core::{FieldEvent, FusionEngine, InferenceQuery, Modality, PrivacyClass};
use rufield_fusion::RuFieldFusion;
use rufield_provenance::{is_fusable, verify_event};
use wifi_densepose_rufield::{
network_egress_allowed, ScanSource, UltrasonicScan, ULTRASONIC_EGRESS_CLASS,
};
const SCAN: &str = include_str!("fixtures/batvu_living_room.ultrasonic.jsonl");
fn scan() -> UltrasonicScan {
UltrasonicScan::load(SCAN, "living_room", ScanSource::Simulated).expect("fixture loads")
}
// ── round-trip ───────────────────────────────────────────────────────────────
#[test]
fn gate_round_trip_every_event_is_well_formed_and_serializes() {
let mut s = scan();
assert_eq!(s.ping_count(), 72);
assert_eq!(s.device_id(), "batvu-reference-01");
assert!(!s.calibration_id().is_empty());
let events = s.events().expect("events");
assert_eq!(events.len(), 72);
let mut previous = 0u64;
for event in &events {
event
.validate_evidence_at(event.timestamp_ns)
.expect("structural evidence invariants hold");
assert_eq!(event.tensor.modality, Modality::Ultrasonic);
assert_eq!(event.sensor.vendor, "batvu");
assert_eq!(event.observation.zone_id.as_deref(), Some("living_room"));
// Every profile value finite and non-negative. `FieldTensor::validate`
// checks only shape and axis rank, so a NaN would serialize to JSON
// `null` and then fail to deserialize as an f32 on the far side of the
// wire — the worst place to find it. The adapter rejects it at parse.
assert!(
event
.tensor
.values
.iter()
.all(|v| v.is_finite() && *v >= 0.0),
"profile values are finite and non-negative"
);
// Strictly increasing, which RuField's replay watermark requires in
// every trust mode and silently drops what does not satisfy.
assert!(event.timestamp_ns > previous);
previous = event.timestamp_ns;
// serde round-trip, byte-stable.
let json = serde_json::to_string(event).expect("serializes");
let back: FieldEvent = serde_json::from_str(&json).expect("deserializes");
assert_eq!(*event, back);
}
let mut ids: Vec<&str> = events.iter().map(|e| e.event_id.as_str()).collect();
ids.sort_unstable();
ids.dedup();
assert_eq!(ids.len(), events.len(), "event ids are unique");
}
// ── fusability ───────────────────────────────────────────────────────────────
#[test]
fn gate_every_event_carries_a_signature_that_verifies() {
let mut s = scan();
let events = s.events().expect("events");
for event in &events {
verify_event(event).expect("ed25519 signature verifies");
assert!(is_fusable(event));
}
// And tampering breaks it, so the signature is load-bearing rather than
// decorative.
let mut tampered = events[0].clone();
tampered.tensor.values[0] = 999.0;
assert!(verify_event(&tampered).is_err());
}
#[test]
fn gate_fusion_ingests_every_event() {
let mut s = scan();
let mut engine = RuFieldFusion::new();
for event in s.events().expect("events") {
engine.ingest(event).expect("fusion accepts the event");
}
}
// ── privacy safety — the correctness item ────────────────────────────────────
#[test]
fn gate_coarse_scan_passes_the_egress_gate_intact() {
// The claim the module makes: configuring the adapter for the coarse output
// means the egress gate has nothing left to catch. If a submodule bump ever
// changes the adapter's default class, this is where it surfaces.
let mut s = scan();
let all = s.events().expect("events").len();
let mut s = scan();
let egress = s.egress_events().expect("egress events").len();
assert_eq!(all, 72);
assert_eq!(
egress, all,
"no event is dropped at the gate in coarse mode"
);
}
#[test]
fn gate_every_event_is_p1_on_both_tensor_and_observation() {
let mut s = scan();
for event in s.events().expect("events") {
assert_eq!(event.tensor.privacy_class, ULTRASONIC_EGRESS_CLASS);
assert_eq!(event.observation.privacy_class, ULTRASONIC_EGRESS_CLASS);
// Both, because the guard is conjunctive over the pair — a P0 tensor
// under a P1 observation is exactly the composite leak the default
// guard exists to close.
assert!(network_egress_allowed(event.tensor.privacy_class, false));
assert!(network_egress_allowed(
event.observation.privacy_class,
false
));
}
assert_eq!(ULTRASONIC_EGRESS_CLASS, PrivacyClass::P1);
}
#[test]
fn gate_ultrasonic_can_never_reach_the_identity_tiers() {
// P5 is only reachable through `identity_evidence`, which
// `validate_evidence_at` restricts to BLE advertisement RSSI — so an
// ultrasonic event carrying it is a hard validation failure rather than a
// policy question. The ceiling is structural.
let mut s = scan();
for event in s.events().expect("events") {
assert!(event.tensor.privacy_class < PrivacyClass::P4);
assert!(event.observation.privacy_class < PrivacyClass::P4);
assert!(event.observation.identity_evidence.is_none());
assert!(event.observation.channel_sounding_provenance.is_none());
}
}
#[test]
fn gate_no_event_claims_a_person() {
// The tempting mistake, refused deliberately. `presence` is one of exactly
// six feature keys the fusion window reads, and populating it would light
// up the shipped `person_present` rule. One transducer pair cannot
// distinguish a person from a coat over the back of a chair.
let mut s = scan();
for event in s.events().expect("events") {
for forbidden in ["presence", "breathing_band", "posture_height", "transient"] {
assert!(
!event.observation.features.contains_key(forbidden),
"an ultrasonic event must not claim `{forbidden}`"
);
}
for label in &event.observation.labels {
assert!(
!label.contains("person") && !label.contains("presence"),
"unexpected personhood label: {label}"
);
}
}
}
/// The honest negative result, asserted rather than avoided.
///
/// Because nothing claims presence, a BatVu scan produces no fused inferences
/// under the shipped rules. Two independent reasons, and pinning both matters
/// because fixing only the first would look like progress and change nothing:
/// no rule lists `"ultrasonic"` among its inputs, and the engine's feature
/// vocabulary is entirely statements about a body, so `range_m` has nothing to
/// drive. RuField v0.1 has no predicate for static geometry.
#[test]
fn gate_no_inferences_and_that_is_the_correct_outcome() {
let mut s = scan();
let mut engine = RuFieldFusion::new();
for event in s.events().expect("events") {
engine.ingest(event).expect("ingest");
}
let inferences = engine
.infer(&InferenceQuery {
zone_id: Some("living_room".into()),
labels: vec![],
track_id: None,
as_of_ns: None,
})
.expect("infer");
assert!(
inferences.is_empty(),
"no shipped rule can fire on a range-only sensor: {inferences:?}"
);
}
// ── trust tier ───────────────────────────────────────────────────────────────
#[test]
fn gate_a_recording_cannot_relabel_itself_into_a_higher_trust_tier() {
// The fixture declares `simulated`. An operator pointing a capture-trusting
// deployment at it gets a hard refusal rather than a silently upgraded
// tier — and the reverse is refused too, so neither direction is a quiet
// reinterpretation.
let err = UltrasonicScan::load(SCAN, "living_room", ScanSource::DeviceCapture)
.expect_err("must refuse");
assert!(
err.to_string().contains("device_capture"),
"the refusal names the mismatch: {err}"
);
}
#[test]
fn gate_simulated_recordings_are_marked_synthetic() {
// Not cosmetic: `synthetic: true` is what keeps simulator output out of
// captured-replay and production trust, which reject it before any key
// lookup. Marking it otherwise to get it accepted is the §11 invariant
// violation ADR-262 forbids.
let mut s = scan();
for event in s.events().expect("events") {
assert!(event.provenance.synthetic);
}
}
// ── determinism ──────────────────────────────────────────────────────────────
#[test]
fn gate_same_recording_yields_a_byte_identical_event_stream() {
let mut a = scan();
let mut b = scan();
let left = serde_json::to_string(&a.events().expect("events")).expect("serializes");
let right = serde_json::to_string(&b.events().expect("events")).expect("serializes");
assert_eq!(left, right);
}
#[test]
fn gate_a_malformed_recording_is_refused_whole() {
// No partial ingest. A stream that half-replays and then dies is the worst
// outcome for a consumer, because it has already acted on the good prefix.
let mut bad = SCAN.lines().take(4).collect::<Vec<_>>().join("\n");
bad.push_str("\n{\"timestamp\":1756162800,\"source\":\"simulated\",\"device_id\":\"x\"}\n");
let err =
UltrasonicScan::load(&bad, "living_room", ScanSource::Simulated).expect_err("must refuse");
assert!(err.to_string().contains("rejected"));
}

View File

@@ -110,7 +110,7 @@ rand = "0.8"
# client (ADR-115 §10 references). `rustls` is preferred over openssl on
# Windows to keep parity with the rest of the workspace (`ureq` above also
# uses rustls).
rumqttc = { version = "0.24", default-features = false, features = ["use-rustls"], optional = true }
rumqttc = { package = "rumqttc-v4-next", version = "0.34", default-features = false, features = ["use-rustls-ring"], optional = true }
# `otel` feature — OTLP log export (`telemetry` module). Same gating
# principle as `mqtt`: the heavy exporter stack (opentelemetry SDK +

View File

@@ -41,7 +41,7 @@ use wifi_densepose_signal::ruvsense::fusion_quality::CalibrationId;
use wifi_densepose_signal::ruvsense::multistatic::MultistaticConfig;
use wifi_densepose_worldgraph::WorldId;
use super::multistatic_bridge::node_frames_from_states;
use super::multistatic_bridge::node_frames_from_states_with_guard;
use super::NodeState;
/// Minimum spacing between engine-error warn logs (errors are still counted
@@ -53,6 +53,8 @@ const ENGINE_ERROR_WARN_INTERVAL: Duration = Duration::from_secs(10);
/// live sensing loop publishes beliefs into.
pub struct EngineBridge {
engine: StreamingEngine,
/// Hard timestamp guard shared by cohort selection and engine validation.
guard_interval_us: u64,
room: WorldId,
/// Nodes already wired into the WorldGraph as sensors (by `node_id`).
registered_nodes: HashMap<u8, WorldId>,
@@ -94,6 +96,11 @@ impl EngineBridge {
room_name: &str,
multistatic_cfg: Option<MultistaticConfig>,
) -> Self {
let guard_interval_us = multistatic_cfg
.as_ref()
.map_or_else(|| MultistaticConfig::default().guard_interval_us, |cfg| {
cfg.guard_interval_us
});
let mut engine = StreamingEngine::new(mode, model_version, GeoRegistration::default());
if let Some(cfg) = multistatic_cfg {
engine.set_multistatic_config(cfg);
@@ -101,6 +108,7 @@ impl EngineBridge {
let room = engine.add_room(room_area_id, room_name);
Self {
engine,
guard_interval_us,
room,
registered_nodes: HashMap::new(),
calibration: CalibrationId(0x5256_0001), // "RV\0\x01" — placeholder epoch
@@ -165,7 +173,8 @@ impl EngineBridge {
node_states: &HashMap<u8, NodeState>,
now_ms: i64,
) -> Option<Result<TrustedOutput, EngineError>> {
let frames = node_frames_from_states(node_states);
let frames =
node_frames_from_states_with_guard(node_states, self.guard_interval_us);
if frames.is_empty() {
return None;
}
@@ -195,7 +204,15 @@ impl EngineBridge {
node_states: &HashMap<u8, NodeState>,
now_ms: i64,
) -> Option<TrustedOutput> {
match self.process_cycle_from_states(node_states, now_ms)? {
let result = self.process_cycle_from_states(node_states, now_ms)?;
self.record_cycle_result(result)
}
fn record_cycle_result(
&mut self,
result: Result<TrustedOutput, EngineError>,
) -> Option<TrustedOutput> {
match result {
Ok(trust) => {
self.last_witness = Some(trust.witness);
self.recalibration_recommended = trust.recalibration_recommended;
@@ -419,45 +436,29 @@ mod tests {
assert!(!bridge.suppress_raw_outputs());
}
/// Error wiring (review finding 1a): a live cycle that fails fusion yields
/// an `EngineError` — previously dropped by `if let Some(Ok(..))` at the
/// call sites. The counter must increment and the last good trust state
/// must survive a later failure.
///
/// Originally this forced the failure with a 56-vs-30 subcarrier mismatch
/// (`DimensionMismatch`). Since #1170 the live bridge canonicalizes every
/// node onto the 56-tone grid, so heterogeneous counts now fuse cleanly —
/// a frame-timestamp spread wider than the fuser's 60 ms guard interval is
/// the remaining deterministic way to provoke a fusion error here.
/// Error-result accounting is independent from live cohort selection, so
/// a future engine error remains auditable without deliberately forwarding
/// temporally incoherent frames through the production bridge.
#[test]
fn observe_cycle_counts_engine_errors() {
// Both nodes are 56-subcarrier (canonicalization-clean), but their
// frame timestamps are 500 ms apart — far beyond the 60 ms guard —
// so the fuser rejects the cycle with TimestampMismatch. Future
// offsets keep both instants safely after the bridge's lazy EPOCH.
fn mismatched_states() -> HashMap<u8, NodeState> {
let now = Instant::now();
let mut a = node_state_with_history(1.0, 56);
a.last_frame_time = Some(now + std::time::Duration::from_millis(600));
let mut b = node_state_with_history(1.05, 56);
b.last_frame_time = Some(now + std::time::Duration::from_millis(100));
let mut m = HashMap::new();
m.insert(0u8, a);
m.insert(1u8, b);
m
}
let mut bridge = EngineBridge::new(PrivacyMode::PrivateHome, 1, "r", "R", None);
let mismatched = mismatched_states();
let error = || {
EngineError::Fusion(
wifi_densepose_signal::ruvsense::multistatic::MultistaticError::TimestampMismatch {
spread_us: 500_000,
guard_us: 60_000,
},
)
};
assert!(bridge.observe_cycle(&mismatched, 1_000).is_none());
assert!(bridge.record_cycle_result(Err(error())).is_none());
assert_eq!(bridge.engine_error_count(), 1);
assert!(
bridge.last_trust_witness().is_none(),
"no witness from a failed cycle"
);
assert!(bridge.observe_cycle(&mismatched, 2_000).is_none());
assert!(bridge.record_cycle_result(Err(error())).is_none());
assert_eq!(bridge.engine_error_count(), 2);
// A later good cycle records trust state; the audit count is kept.
@@ -467,11 +468,39 @@ mod tests {
assert_eq!(bridge.engine_error_count(), 2);
// And a subsequent failure keeps the last good witness readable.
assert!(bridge.observe_cycle(&mismatched, 4_000).is_none());
assert!(bridge.record_cycle_result(Err(error())).is_none());
assert_eq!(bridge.engine_error_count(), 3);
assert!(bridge.last_trust_witness().is_some());
}
#[test]
fn governed_cycles_prune_slow_mixed_width_nodes_without_errors() {
let mut bridge = EngineBridge::new(PrivacyMode::PrivateHome, 1, "r", "R", None);
for tick in 0..50_i64 {
let now = Instant::now();
let mut states = HashMap::new();
for (node_id, age_ms, n_sub) in [
(1, 0, 64),
(3, 10, 256),
(4, 50, 64),
(7, 1_000, 256),
] {
let mut node = node_state_with_history(1.0 + node_id as f64 * 0.01, n_sub);
node.last_frame_time = Some(now - Duration::from_millis(age_ms));
states.insert(node_id, node);
}
assert!(
bridge.observe_cycle(&states, 1_000 + tick * 50).is_some(),
"governed cycle {tick}"
);
}
assert_eq!(bridge.engine_error_count(), 0);
assert!(bridge.last_trust_witness().is_some());
}
/// ADR-141 mapping (review finding 1c): a cycle emitted at class
/// Restricted flips `suppress_raw_outputs`, which `main.rs` uses to strip
/// per-node raw amplitude vectors from the live publish — the same field

View File

@@ -286,6 +286,9 @@ struct Esp32Frame {
/// ADR-110 byte 18: PPDU type the CSI was sampled from. Pre-ADR-110
/// firmware sends 0 ⇒ `PpduType::HtLegacy`.
ppdu_type: wifi_densepose_hardware::PpduType,
/// ADR-110 byte 19 metadata, including whether this frame was captured
/// while the node had a valid IEEE 802.15.4 mesh-time solution.
adr018_flags: wifi_densepose_hardware::Adr018Flags,
amplitudes: Vec<f64>,
phases: Vec<f64>,
}
@@ -675,6 +678,12 @@ struct NodeState {
latest_sync: Option<wifi_densepose_hardware::SyncPacket>,
/// Last time a sync packet from this node was received (for staleness).
latest_sync_at: Option<std::time::Instant>,
/// Sequence number of the newest CSI frame admitted to `frame_history`.
/// Kept alongside the history so multistatic fusion can timestamp the
/// exact sample it consumes, rather than the host's UDP arrival time.
latest_csi_sequence: Option<u32>,
/// Whether byte 19 bit 4 marked that newest admitted CSI frame as synced.
latest_csi_sync_valid: bool,
/// ADR-110 iter 18: EMA-tracked CSI frame rate for this node.
/// Replaces the hardcoded 20 Hz fallback in
/// `mesh_aligned_us_for_csi_frame` once `csi_fps_samples ≥ 5`.
@@ -832,6 +841,9 @@ impl NodeState {
/// staleness gate).
pub(crate) fn mesh_aligned_us(&self, local_at_frame_us: u64) -> Option<u64> {
let sync = self.latest_sync.as_ref()?;
if !sync.flags.is_valid {
return None;
}
let seen_at = self.latest_sync_at?;
// Drop stale syncs — firmware emits at ~0.5 Hz default, anything
// older than 9 s likely means the mesh transport dropped.
@@ -850,10 +862,20 @@ impl NodeState {
/// no fresh sync has been observed for this node.
pub(crate) fn mesh_aligned_us_for_csi_frame(&self, frame_sequence: u32) -> Option<u64> {
let sync = self.latest_sync.as_ref()?;
if !sync.flags.is_valid {
return None;
}
let seen_at = self.latest_sync_at?;
if seen_at.elapsed() > std::time::Duration::from_secs(9) {
return None;
}
// A recently-received sync datagram can overtake an older CSI
// datagram in UDP delivery order. Only extrapolate forward (including
// a genuine u32 wrap); otherwise fall back to host arrival time.
let delta_frames = frame_sequence.wrapping_sub(sync.sequence);
if delta_frames > i32::MAX as u32 {
return None;
}
// Iter 18: use the measured per-node fps once we have ≥5 inter-frame
// samples; until then fall back to the 20 Hz firmware ceiling. The
// §A0.12 capture showed real bench fps ≈ 10, so the measured value
@@ -862,6 +884,16 @@ impl NodeState {
Some(sync.mesh_aligned_us_for_sequence(frame_sequence, fps))
}
/// Mesh timestamp for the newest CSI frame admitted to `frame_history`.
/// Both the frame-level sync-valid bit and a fresh, valid sync packet are
/// required; callers retain their existing host-arrival fallback.
pub(crate) fn mesh_aligned_us_for_latest_csi_frame(&self) -> Option<u64> {
if !self.latest_csi_sync_valid {
return None;
}
self.mesh_aligned_us_for_csi_frame(self.latest_csi_sequence?)
}
/// ADR-110 iter 18 — update the per-node observed-fps EMA from a fresh
/// CSI frame arrival. Call once per accepted CSI frame from
/// `udp_receiver_task`. Uses `last_frame_time` as the previous-frame
@@ -927,6 +959,21 @@ impl NodeState {
first_sensing_frame
}
/// Record an accepted CSI sample and preserve the wire metadata needed by
/// the multistatic bridge to recover capture time. Grid-rejected frames
/// intentionally use `observe_csi_frame_arrival` directly because they do
/// not replace the sample at the back of `frame_history`.
pub(crate) fn observe_accepted_csi_frame(
&mut self,
sequence: u32,
sync_valid: bool,
now: std::time::Instant,
) -> bool {
self.latest_csi_sequence = Some(sequence);
self.latest_csi_sync_valid = sync_valid;
self.observe_csi_frame_arrival(now)
}
pub(crate) fn new() -> Self {
Self {
frame_history: VecDeque::new(),
@@ -951,6 +998,8 @@ impl NodeState {
edge_vitals: None,
latest_sync: None,
latest_sync_at: None,
latest_csi_sequence: None,
latest_csi_sync_valid: false,
csi_fps_ema: 20.0,
csi_fps_samples: 0,
latest_features: None,
@@ -1945,7 +1994,8 @@ fn parse_esp32_frame(buf: &[u8]) -> Option<Esp32Frame> {
// [12..15] sequence (u32 LE)
// [16] rssi (i8)
// [17] noise_floor (i8)
// [18..19] reserved
// [18] PPDU type
// [19] ADR-018 flags (bit 4 = IEEE 802.15.4 sync valid)
// [20..] I/Q data
// Issue #1005: until 2026-06 this code read n_subcarriers from byte 6
// alone (an ESP32-C6 HE-SU frame's 256 = 0x0100 LE decoded as 0 — the
@@ -1966,6 +2016,7 @@ fn parse_esp32_frame(buf: &[u8]) -> Option<Esp32Frame> {
};
let noise_floor = buf[17] as i8;
let ppdu_type = wifi_densepose_hardware::PpduType::from_byte(buf[18]);
let adr018_flags = wifi_densepose_hardware::Adr018Flags::from_byte(buf[19]);
let iq_start = 20;
let n_pairs = n_antennas as usize * n_subcarriers as usize;
@@ -1995,6 +2046,7 @@ fn parse_esp32_frame(buf: &[u8]) -> Option<Esp32Frame> {
rssi,
noise_floor,
ppdu_type,
adr018_flags,
amplitudes,
phases,
})
@@ -2024,7 +2076,7 @@ mod issue_1009_n_subcarriers_u16_tests {
buf[16] = (-40i8) as u8; // rssi
buf[17] = (-90i8) as u8; // noise_floor
buf[18] = 0; // ppdu_type
buf[19] = 0;
buf[19] = 0x10; // ADR-018: IEEE 802.15.4 sync valid
for k in 0..n_subcarriers as usize {
buf[20 + k * 2] = (5 + (k % 40) as i8) as u8; // i
buf[20 + k * 2 + 1] = (k % 30) as u8; // q
@@ -2047,6 +2099,7 @@ mod issue_1009_n_subcarriers_u16_tests {
assert_eq!(frame.node_id, 7);
assert_eq!(frame.rssi, -40);
assert_eq!(frame.sequence, 42);
assert!(frame.adr018_flags.ieee802154_sync_valid);
}
#[test]
@@ -2941,6 +2994,7 @@ async fn windows_wifi_task(state: SharedState, tick_ms: u64) {
rssi: first_rssi.clamp(-128.0, 127.0) as i8,
noise_floor: -90,
ppdu_type: wifi_densepose_hardware::PpduType::HtLegacy,
adr018_flags: wifi_densepose_hardware::Adr018Flags::default(),
amplitudes: multi_ap_frame.amplitudes.clone(),
phases: multi_ap_frame.phases.clone(),
};
@@ -3129,6 +3183,7 @@ async fn windows_wifi_fallback_tick(state: &SharedState, seq: u32) {
rssi: rssi_dbm as i8,
noise_floor: -90,
ppdu_type: wifi_densepose_hardware::PpduType::HtLegacy,
adr018_flags: wifi_densepose_hardware::Adr018Flags::default(),
amplitudes: vec![signal_pct],
phases: vec![0.0],
};
@@ -3504,6 +3559,7 @@ fn generate_simulated_frame(tick: u64) -> Esp32Frame {
rssi: (-40.0 + 5.0 * (t * 0.2).sin()) as i8,
noise_floor: -90,
ppdu_type: wifi_densepose_hardware::PpduType::HtLegacy,
adr018_flags: wifi_densepose_hardware::Adr018Flags::default(),
amplitudes,
phases,
}
@@ -6702,8 +6758,11 @@ async fn udp_receiver_task(
// ADR-110 iter 19 — feed the per-node fps EMA from real
// CSI arrivals. The helper sets `last_frame_time` as a
// side effect, so the previous bare assignment is gone.
let first_sensing_frame =
ns.observe_csi_frame_arrival(std::time::Instant::now());
let first_sensing_frame = ns.observe_accepted_csi_frame(
frame.sequence,
frame.adr018_flags.ieee802154_sync_valid,
std::time::Instant::now(),
);
if first_sensing_frame && telemetry::curated_events_enabled() {
info!(name: semconv::EVENT_RUVIEW_NODE_ONLINE, { "ruview.node.id" = node_id }, "node {node_id} online (CSI)");
}
@@ -9327,6 +9386,31 @@ mod sync_snapshot_helper_tests {
"10 s old sync must trigger the 9 s staleness gate");
}
#[test]
fn latest_csi_mesh_time_requires_both_validity_signals() {
let now = std::time::Instant::now();
let mut ns = NodeState::new();
ns.apply_sync_packet(populated_sync(9), now);
ns.observe_accepted_csi_frame(21, false, now);
assert!(
ns.mesh_aligned_us_for_latest_csi_frame().is_none(),
"an unsynchronized CSI capture must use the host-time fallback"
);
ns.observe_accepted_csi_frame(21, true, now + std::time::Duration::from_millis(50));
assert_eq!(
ns.mesh_aligned_us_for_latest_csi_frame(),
Some(27_684_885)
);
ns.latest_sync.as_mut().unwrap().flags.is_valid = false;
assert!(
ns.mesh_aligned_us_for_latest_csi_frame().is_none(),
"an invalid sync packet must not timestamp even a flagged CSI frame"
);
}
#[test]
fn snapshot_reflects_leader_state() {
// Same data shape that /api/v1/mesh emits for a leader node.

View File

@@ -30,7 +30,10 @@
use std::sync::Arc;
use std::time::{Duration, Instant};
use rumqttc::{AsyncClient, ClientError, EventLoop, MqttOptions, QoS, Transport, TlsConfiguration};
use rumqttc::{
AsyncClient, ClientError, EventLoop, MqttOptions, PublishOptions, QoS, Transport,
TlsConfiguration,
};
use tokio::sync::broadcast;
use tokio::task::JoinHandle;
use tracing::{error, info, warn};
@@ -70,14 +73,14 @@ const NODE_SNAPSHOT_STALE_AFTER: Duration = Duration::from_secs(10);
/// Build a `rumqttc::MqttOptions` from validated [`MqttConfig`].
fn build_mqtt_options(cfg: &MqttConfig) -> MqttOptions {
let mut opts = MqttOptions::new(&cfg.client_id, &cfg.host, cfg.port);
opts.set_keep_alive(Duration::from_secs(30));
let mut opts = MqttOptions::new(&cfg.client_id, (cfg.host.as_str(), cfg.port));
opts.set_keep_alive(30);
opts.set_clean_session(true);
if let (Some(u), Some(p)) = (cfg.username.as_deref(), cfg.password.as_deref()) {
opts.set_credentials(u, p);
opts.set_credentials(u.to_owned(), p.as_bytes().to_vec());
} else if let Some(u) = cfg.username.as_deref() {
opts.set_credentials(u, "");
opts.set_credentials(u.to_owned(), Vec::<u8>::new());
}
opts.set_transport(build_transport(&cfg.tls));
@@ -223,7 +226,8 @@ async fn run(
mut state_rx: broadcast::Receiver<VitalsSnapshot>,
) {
let opts = build_mqtt_options(&cfg);
let (client, mut eventloop): (AsyncClient, EventLoop) = AsyncClient::new(opts, 256);
let (client, mut eventloop): (AsyncClient, EventLoop) =
AsyncClient::builder(opts).capacity(256).build();
let entities = DiscoveryBuilder::enabled_entities(
cfg.privacy_mode,
@@ -369,7 +373,13 @@ async fn publish_all_discovery(
let cfg = b.build(e);
let topic = b.config_topic(e);
let payload = serde_json::to_string(&cfg).expect("discovery payload always serialises");
client.publish(&topic, QoS::AtLeastOnce, true, payload).await?;
client
.publish(
&topic,
payload,
PublishOptions::new(QoS::AtLeastOnce).retained(),
)
.await?;
}
Ok(())
}
@@ -380,7 +390,13 @@ async fn publish_availability(
state: &str,
) -> Result<(), ClientError> {
for topic in &avail.online_topics {
client.publish(topic, QoS::AtLeastOnce, true, state).await?;
client
.publish(
topic,
state,
PublishOptions::new(QoS::AtLeastOnce).retained(),
)
.await?;
}
Ok(())
}
@@ -441,7 +457,13 @@ async fn publish_state(client: &AsyncClient, m: &StateMessage) -> Result<(), Cli
1 => QoS::AtLeastOnce,
_ => QoS::ExactlyOnce,
};
client.publish(&m.topic, qos, m.retain, m.payload.clone()).await
client
.publish(
&m.topic,
m.payload.clone(),
PublishOptions::new(qos).retain(m.retain),
)
.await
}
#[cfg(test)]

View File

@@ -12,7 +12,9 @@ use std::time::{Duration, Instant};
use wifi_densepose_signal::hardware_norm::{CanonicalCsiFrame, HardwareNormalizer, HardwareType};
use wifi_densepose_signal::ruvsense::multiband::MultiBandCsiFrame;
use wifi_densepose_signal::ruvsense::multistatic::{FusedSensingFrame, MultistaticFuser};
use wifi_densepose_signal::ruvsense::multistatic::{
FusedSensingFrame, MultistaticConfig, MultistaticFuser,
};
use super::NodeState;
@@ -24,7 +26,13 @@ const DEFAULT_FREQ_MHZ: u32 = 2437; // Channel 6
/// Monotonic reference point for timestamp generation. All node timestamps
/// are relative to this instant, avoiding wall-clock/monotonic mixing issues.
static EPOCH: LazyLock<Instant> = LazyLock::new(Instant::now);
/// Backdate the lazy initialization beyond the active-node window so frames
/// recorded just before the first bridge call retain their arrival-time skew.
static EPOCH: LazyLock<Instant> = LazyLock::new(|| {
Instant::now()
.checked_sub(STALE_THRESHOLD + STALE_THRESHOLD)
.unwrap_or_else(Instant::now)
});
/// Shared length-only canonicalizer (issue #1170). The default 56-tone grid
/// matches what `MultistaticFuser` (ADR-154) expects. Stateless and immutable,
@@ -38,6 +46,24 @@ static NORMALIZER: LazyLock<HardwareNormalizer> = LazyLock::new(HardwareNormaliz
/// `last_frame_time`.
pub fn node_frame_from_state(node_id: u8, ns: &NodeState) -> Option<MultiBandCsiFrame> {
let last_time = ns.last_frame_time.as_ref()?;
let timestamp_us = ns
.mesh_aligned_us_for_latest_csi_frame()
.unwrap_or_else(|| host_arrival_timestamp_us(last_time));
node_frame_from_state_at(node_id, ns, timestamp_us)
}
fn host_arrival_timestamp_us(last_time: &Instant) -> u64 {
last_time
.checked_duration_since(*EPOCH)
.unwrap_or_default()
.as_micros() as u64
}
fn node_frame_from_state_at(
node_id: u8,
ns: &NodeState,
timestamp_us: u64,
) -> Option<MultiBandCsiFrame> {
let latest = ns.frame_history.back()?;
if latest.is_empty() {
return None;
@@ -54,11 +80,6 @@ pub fn node_frame_from_state(node_id: u8, ns: &NodeState) -> Option<MultiBandCsi
let n_sub = amplitude.len();
let phase = vec![0.0_f32; n_sub];
// Monotonic timestamp: microseconds since a shared process-local epoch.
// All nodes use the same reference so the fuser's guard_interval_us check
// compares apples to apples. No wall-clock mixing (immune to NTP jumps).
let timestamp_us = last_time.duration_since(*EPOCH).as_micros() as u64;
let canonical = CanonicalCsiFrame {
amplitude,
phase,
@@ -74,25 +95,91 @@ pub fn node_frame_from_state(node_id: u8, ns: &NodeState) -> Option<MultiBandCsi
})
}
/// Collect `MultiBandCsiFrame`s from all active nodes.
/// Collect the default-guard coherent `MultiBandCsiFrame` cohort.
///
/// A node is considered active if its `last_frame_time` is within
/// [`STALE_THRESHOLD`] of `now`.
pub fn node_frames_from_states(node_states: &HashMap<u8, NodeState>) -> Vec<MultiBandCsiFrame> {
let now = Instant::now();
let mut frames = Vec::with_capacity(node_states.len());
node_frames_from_states_with_guard(
node_states,
MultistaticConfig::default().guard_interval_us,
)
}
for (&node_id, ns) in node_states {
// Skip stale nodes
if let Some(ref t) = ns.last_frame_time {
if now.duration_since(*t) > STALE_THRESHOLD {
continue;
}
} else {
/// Collect the freshest temporally coherent cohort of active node frames.
///
/// Nodes can publish at very different rates (for example, a mixed S3/C6
/// fleet). `STALE_THRESHOLD` determines whether a node is alive; it does not
/// mean its latest frame belongs to the current sensing cycle. After choosing
/// one timestamp domain for the whole cycle, retain only frames within the
/// fuser's hard guard of the freshest frame. This prevents a slow-but-live node
/// from turning every governed cycle into `TimestampMismatch`, while always
/// preserving at least the freshest node for the supported single-node path.
pub fn node_frames_from_states_with_guard(
node_states: &HashMap<u8, NodeState>,
guard_interval_us: u64,
) -> Vec<MultiBandCsiFrame> {
let now = Instant::now();
let mut active: Vec<(u8, &NodeState)> = node_states
.iter()
.filter_map(|(&node_id, ns)| {
let last_time = ns.last_frame_time.as_ref()?;
(now.duration_since(*last_time) <= STALE_THRESHOLD).then_some((node_id, ns))
})
.collect();
active.sort_unstable_by_key(|(node_id, _)| *node_id);
if active.is_empty() {
return Vec::new();
}
let guard_interval_us = guard_interval_us.max(1);
// Timestamp domains must be selected for the cycle as a whole. A CSI
// frame can legitimately arrive between periodic sync-marked frames. If
// that one node fell back to process-local host time while a peer retained
// mesh epoch time, the resulting hundreds-of-seconds spread made every
// governed fusion cycle fail. Use mesh time only when every active node
// can provide it; otherwise use host-arrival time consistently for all.
let mesh_times: Option<Vec<u64>> = active
.iter()
.map(|(_, ns)| ns.mesh_aligned_us_for_latest_csi_frame())
.collect::<Option<Vec<_>>>()
.filter(|times| {
let Some(min) = times.iter().min() else {
return false;
};
let Some(max) = times.iter().max() else {
return false;
};
max.saturating_sub(*min) <= guard_interval_us
});
let mut timed = Vec::with_capacity(active.len());
for (index, (node_id, ns)) in active.into_iter().enumerate() {
let timestamp_us = mesh_times.as_ref().map_or_else(
|| {
host_arrival_timestamp_us(
ns.last_frame_time.as_ref().expect("active node has time"),
)
},
|times| times[index],
);
timed.push((node_id, ns, timestamp_us));
}
let freshest_timestamp_us = timed
.iter()
.map(|(_, _, timestamp_us)| *timestamp_us)
.max()
.expect("non-empty active cohort");
let mut frames = Vec::with_capacity(timed.len());
for (node_id, ns, timestamp_us) in timed {
if freshest_timestamp_us.saturating_sub(timestamp_us) > guard_interval_us {
continue;
}
if let Some(frame) = node_frame_from_state(node_id, ns) {
if let Some(frame) = node_frame_from_state_at(node_id, ns, timestamp_us) {
frames.push(frame);
}
}
@@ -111,7 +198,8 @@ pub fn fuse_or_fallback(
node_states: &HashMap<u8, NodeState>,
dedup_factor: f64,
) -> (Option<FusedSensingFrame>, Option<usize>) {
let frames = node_frames_from_states(node_states);
let frames =
node_frames_from_states_with_guard(node_states, fuser.guard_interval_us());
if frames.is_empty() {
return (None, Some(0));
}
@@ -173,6 +261,7 @@ pub fn compute_person_score_from_amplitudes(amplitudes: &[f32]) -> f64 {
mod tests {
use super::*;
use std::collections::VecDeque;
use wifi_densepose_hardware::{SyncPacket, SyncPacketFlags};
/// Helper: build a minimal NodeState for testing. Uses `NodeState::new()`
/// then mutates the `pub(crate)` fields the bridge needs.
@@ -225,6 +314,200 @@ mod tests {
assert_eq!(ch.hardware_type, HardwareType::Esp32S3);
}
fn mark_mesh_timed_frame(
ns: &mut NodeState,
node_id: u8,
sync_sequence: u32,
frame_sequence: u32,
mesh_epoch_us: u64,
host_arrival: Instant,
) {
ns.apply_sync_packet(
SyncPacket {
node_id,
proto_ver: 1,
flags: SyncPacketFlags {
is_leader: node_id == 1,
is_valid: true,
smoothed_used: node_id != 1,
},
local_us: 10_000_000,
epoch_us: mesh_epoch_us,
sequence: sync_sequence,
},
Instant::now(),
);
ns.observe_accepted_csi_frame(frame_sequence, true, host_arrival);
}
#[test]
fn mesh_timestamp_replaces_skewed_host_arrival_time() {
let mut history = VecDeque::new();
history.push_back(vec![10.0, 20.0, 30.0]);
let host_arrival = Instant::now();
let mut ns = make_node_state(history, None, 0);
mark_mesh_timed_frame(&mut ns, 1, 100, 101, 1_000_000, host_arrival);
let frame = node_frame_from_state(1, &ns).expect("mesh-timed frame");
assert_eq!(frame.timestamp_us, 1_050_000);
}
#[test]
fn mesh_time_allows_fusion_despite_udp_arrival_skew() {
let base = Instant::now() - Duration::from_millis(500);
let mut states = HashMap::new();
let mut first_history = VecDeque::new();
first_history.push_back(vec![1.0; 64]);
let mut first = make_node_state(first_history, None, 0);
mark_mesh_timed_frame(&mut first, 1, 100, 101, 1_000_000, base);
states.insert(1, first);
let mut second_history = VecDeque::new();
second_history.push_back(vec![1.1; 64]);
let mut second = make_node_state(second_history, None, 0);
mark_mesh_timed_frame(
&mut second,
2,
200,
201,
1_005_000,
base + Duration::from_millis(200),
);
states.insert(2, second);
let frames = node_frames_from_states(&states);
let spread = frames.iter().map(|f| f.timestamp_us).max().unwrap()
- frames.iter().map(|f| f.timestamp_us).min().unwrap();
assert_eq!(spread, 5_000, "mesh capture spread, not 200 ms UDP skew");
assert!(
MultistaticFuser::new().fuse(&frames).is_ok(),
"mesh-aligned frames inside the 60 ms guard must fuse"
);
}
#[test]
fn partial_sync_uses_one_host_timestamp_domain_for_the_cycle() {
let base = Instant::now() - Duration::from_millis(500);
let mut states = HashMap::new();
let mut synced_history = VecDeque::new();
synced_history.push_back(vec![1.0; 64]);
let mut synced = make_node_state(synced_history, None, 0);
mark_mesh_timed_frame(&mut synced, 1, 100, 101, 500_000_000, base);
states.insert(1, synced);
let mut unsynced_history = VecDeque::new();
unsynced_history.push_back(vec![1.1; 64]);
states.insert(
2,
make_node_state(unsynced_history, Some(base + Duration::from_millis(5)), 0),
);
let frames = node_frames_from_states(&states);
let spread = frames.iter().map(|f| f.timestamp_us).max().unwrap()
- frames.iter().map(|f| f.timestamp_us).min().unwrap();
assert_eq!(spread, 5_000, "partial sync must fall back as one cycle");
assert!(
MultistaticFuser::new().fuse(&frames).is_ok(),
"mixed sync validity must not mix mesh and host timestamp domains"
);
}
#[test]
fn incoherent_mesh_timestamps_fall_back_to_host_arrival_for_the_cycle() {
let base = Instant::now() - Duration::from_millis(500);
let mut states = HashMap::new();
for (node_id, mesh_epoch_us, arrival) in [
(1, 1_000_000, base),
(2, 500_000_000, base + Duration::from_millis(5)),
] {
let mut history = VecDeque::new();
history.push_back(vec![1.0; 64]);
let mut state = make_node_state(history, None, 0);
mark_mesh_timed_frame(&mut state, node_id, 100, 101, mesh_epoch_us, arrival);
states.insert(node_id, state);
}
let frames = node_frames_from_states(&states);
let spread = frames.iter().map(|f| f.timestamp_us).max().unwrap()
- frames.iter().map(|f| f.timestamp_us).min().unwrap();
assert_eq!(spread, 5_000, "incoherent mesh time must not reach fusion");
assert!(MultistaticFuser::new().fuse(&frames).is_ok());
}
#[test]
fn unsynchronized_frames_prune_to_freshest_host_cohort() {
let base = Instant::now() - Duration::from_millis(500);
let mut states = HashMap::new();
for (node_id, arrival) in [(1, base), (2, base + Duration::from_millis(200))] {
let mut history = VecDeque::new();
history.push_back(vec![1.0; 64]);
states.insert(node_id, make_node_state(history, Some(arrival), 0));
}
let frames = node_frames_from_states(&states);
assert_eq!(frames.len(), 1, "only the freshest host frame is coherent");
assert_eq!(frames[0].node_id, 2);
assert!(
MultistaticFuser::new().fuse(&frames).is_ok(),
"an asynchronous slow node must not fail the live cycle"
);
}
#[test]
fn slow_live_node_is_excluded_from_fresh_cohort() {
let now = Instant::now();
let mut states = HashMap::new();
for (node_id, age_ms, n_sub) in [
(1, 0, 64),
(3, 10, 256),
(4, 50, 64),
(7, 1_000, 256),
] {
let mut history = VecDeque::new();
history.push_back(vec![1.0 + node_id as f64 * 0.01; n_sub]);
states.insert(
node_id,
make_node_state(
history,
Some(now - Duration::from_millis(age_ms)),
1,
),
);
}
let frames = node_frames_from_states_with_guard(&states, 60_000);
let ids: Vec<u8> = frames.iter().map(|frame| frame.node_id).collect();
assert_eq!(ids, vec![1, 3, 4]);
assert!(MultistaticFuser::new().fuse(&frames).is_ok());
}
#[test]
fn configured_guard_is_shared_with_cohort_selection() {
let base = Instant::now() - Duration::from_millis(500);
let mut states = HashMap::new();
for (node_id, arrival) in [
(1, base),
(2, base + Duration::from_millis(150)),
] {
let mut history = VecDeque::new();
history.push_back(vec![1.0; 64]);
states.insert(node_id, make_node_state(history, Some(arrival), 0));
}
let cfg = MultistaticConfig {
guard_interval_us: 200_000,
..MultistaticConfig::default()
};
let fuser = MultistaticFuser::with_config(cfg);
let (fused, fallback) = fuse_or_fallback(&fuser, &states, 3.0);
assert_eq!(fused.as_ref().map(|frame| frame.active_nodes), Some(2));
assert!(fallback.is_none());
}
#[test]
fn heterogeneous_node_counts_canonicalize_and_fuse() {
// Issue #1170 regression: a mixed mesh with HT20 (64-bin) and HT40

View File

@@ -104,12 +104,11 @@ async fn subscribe_client(port: u16, topics: &[&str]) -> (AsyncClient, EventLoop
.unwrap_or(0);
let mut opts = MqttOptions::new(
format!("ruview-test-sub-{}-{}", std::process::id(), suffix),
"127.0.0.1",
port,
("127.0.0.1", port),
);
opts.set_keep_alive(Duration::from_secs(10));
opts.set_keep_alive(10);
opts.set_clean_session(true);
let (client, mut eventloop) = AsyncClient::new(opts, 256);
let (client, mut eventloop) = AsyncClient::builder(opts).capacity(256).build();
for t in topics {
client.subscribe(*t, QoS::AtLeastOnce).await.unwrap();
}
@@ -147,7 +146,11 @@ async fn collect_published(
let remain = until - tokio::time::Instant::now();
match timeout(remain, eventloop.poll()).await {
Ok(Ok(Event::Incoming(Packet::Publish(p)))) => {
out.push((p.topic, p.payload.to_vec(), p.retain));
out.push((
String::from_utf8_lossy(&p.topic).to_string(),
p.payload.to_vec(),
p.retain,
));
}
Ok(Ok(_)) => {} // ignore other events
Ok(Err(e)) => {

View File

@@ -272,6 +272,17 @@ impl MultistaticFuser {
self.node_positions = positions;
}
/// Return the configured hard timestamp guard in microseconds.
///
/// Callers that assemble frames before invoking [`Self::fuse`] use this
/// to select one temporally coherent sensing cohort. Keeping selection and
/// validation on the same guard prevents stale low-rate nodes from making
/// every otherwise-live fusion cycle fail.
#[must_use]
pub fn guard_interval_us(&self) -> u64 {
self.config.guard_interval_us
}
/// Return the current node positions.
pub fn node_positions(&self) -> &[[f32; 3]] {
&self.node_positions

2
vendor/rufield vendored