ruview @ v0.3.0-streaming-engine
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- 60.8 MiB
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release notes
RuView Streaming Engine v0.3.0 — Auditable Environmental Intelligence
What this is
Most WiFi-sensing stacks emit a number and hope you trust it. RuView's streaming engine is built so you don't have to. Every conclusion it reaches — "someone is in the living room," "fall risk elevated," "the room layout changed" — carries a full evidence trail: which sensors saw it, how much they agreed, which calibration and model produced it, and what privacy policy it was emitted under.
The throughline is trust. If you ask "why should I believe this when it says a person fell?", the engine answers with signal evidence, sensor agreement, calibration provenance, and an auditable privacy posture — not just a confidence score.
This release lands the ADR-135→146 series: the data contracts, the trust/privacy/audit machinery, and the algorithms — all real, tested, and composed into one end-to-end pipeline cycle.
The two layers that make it auditable
- WorldGraph (
wifi-densepose-worldgraph) — the where & why graph. A typed graph of rooms, sensors, RF links, person tracks, object anchors, events, and beliefs, connected by typed edges:observes,located_in,derived_from,contradicts,privacy_limited_by. The privacy posture is visible in the persisted graph — an auditor can read exactly what was suppressed and why. - Trusted semantic records — the what we believe right now record. Every semantic state carries model version, calibration version, evidence refs, confidence, expiry, and privacy action. High-stakes actions (caregiver escalation) require multi-signal agreement, not a single noisy primitive.
What's new in v0.3.0
| Area | Capability |
|---|---|
| Frame contracts (ADR-136) | ComplexSample (LE-canonical), provenance fields on every frame, CanonicalFrame BLAKE3 witness, Stage/Versioned/QualityScored traits |
| Calibration (ADR-135) | BaselineCalibration::apply() stamps a deterministic calibration_id onto each frame |
| Fusion quality (ADR-137) | QualityScore with per-node weights, evidence refs, and contradiction flags; calibration-mismatch detection |
| Array coordination (ADR-138) | clock-quality + geometry gating; degraded nodes go "watch-only" |
| WorldGraph (ADR-139) | the typed digital twin + privacy rollup + deterministic persistence |
| Semantic records (ADR-140) | auditable state records + multi-signal agent routing |
| Privacy control plane (ADR-141) | named modes + actions + a BLAKE3 hash-chained, tamper-evident attestation |
| Evolution + VoxelMap (ADR-142) | cross-link "the room changed" detection + Bayesian occupancy, privacy-gated to a histogram |
| RF-SLAM (ADR-143) | persistent reflector discovery → learned static anchors |
| UWB fusion (ADR-144) | range-constraint refinement with outlier rejection (forward-looking) |
| Ablation harness (ADR-145) | feature-matrix metrics incl. membership-inference privacy leakage |
| RF encoder (ADR-146) | multi-task heads with per-head uncertainty + contrastive batcher (forward-looking) |
Engine (wifi-densepose-engine) |
the composition root: one process_cycle() runs the whole trust pipeline |
Quick start
use wifi_densepose_engine::StreamingEngine;
use wifi_densepose_bfld::PrivacyMode;
use wifi_densepose_geo::types::GeoRegistration;
use wifi_densepose_signal::ruvsense::fusion_quality::CalibrationId;
// 1. Build the engine with a privacy posture + model version.
let mut engine = StreamingEngine::new(PrivacyMode::PrivateHome, 1, GeoRegistration::default());
// 2. Describe the space (rooms + sensors are WorldGraph nodes).
let room = engine.add_room("living_room", "Living Room");
let sensor = engine.add_sensor("esp32-com9", room);
engine.register_node_geometry(0, 1.0, 0.0, 0.0); // ADR-138 array geometry (optional)
// 3. Each 50 ms cycle: feed per-node CSI frames + the calibration epoch.
let out = engine.process_cycle(&node_frames, CalibrationId(0xABCD), room, now_ms)?;
// 4. The result is a *trusted* belief — fully traceable.
println!("class={:?} demoted={} evidence={:?}",
out.effective_class, out.demoted, out.provenance.evidence);
assert_eq!(out.quality.calibration_id, Some(CalibrationId(0xABCD)));
// 5. Persist the world model; reload reproduces the same query results.
let snapshot = engine.snapshot_json()?; // RVF payload — never raw RF frames
Per-node calibration (mismatch demotes privacy automatically):
let out = engine.process_cycle_calibrated(
&node_frames,
&[Some(CalibrationId(1)), Some(CalibrationId(2))], // disagree → CalibrationIdMismatch
room, now_ms)?;
assert!(out.demoted); // privacy class demoted to Restricted
assert_eq!(out.quality.calibration_id, None); // no single calibration epoch
Validated (acceptance tests that prove the architecture)
- ADR-137
two calibrated frames → calibration mismatch → QualityScore contradiction → Restricted → calibration_id None → witness stable - ADR-139
live_frame → fusion → worldgraph_update → privacy_rollup → persist → reload → same_contents(no raw RF persisted) - ADR-140
raw snapshot → semantic primitive → SemanticStateRecord → agreement rule → expired record rejected - ADR-142
3 links drift 30 frames → ChangePoint → VoxelMap accumulates → low-confidence suppressed → VoxelGate Restricted histogram → ADR-137 contradiction
Performance & safety
- ~6.35 µs per full cycle (4 nodes / 56 subcarriers) — ~7,800× under the 50 ms / 20 Hz budget (criterion:
cargo bench -p wifi-densepose-engine). - New crates are
#![forbid(unsafe_code)]; no hardcoded secrets; input validated at boundaries; privacy demotion is monotonic; mode changes are hash-chain attested. wifi-densepose-coreandwifi-densepose-bfldbuild#![no_std]for the ESP32-S3 on-device path.
Build & test
cd v2
cargo build --release --workspace --no-default-features # optimized build
cargo test --workspace --no-default-features # full suite
cargo test -p wifi-densepose-engine # 13 integration tests
cargo bench -p wifi-densepose-engine # per-cycle latency
Status (honest)
Integrated and validated end-to-end: ADR-135/136/137/138/139/141/142/143 via the
wifi-densepose-engine composition root. Forward-looking / pending: live 20 Hz
sensing-server loop wiring, UWB hardware (ADR-144), and RF-encoder model training
(ADR-146). Each GitHub issue (#840–#850) lists what is Built vs Integration glue.
download
curl -fL -o v0.3.0-streaming-engine.zip https://ratatoskr.space/pkg/ruview/v0.3.0-streaming-engine.zip
printf '%s %s\n' 'cc3c0158279774cc53b2a274351eafab500dbf5e00a8f45d9a286417d0ac7d47' 'v0.3.0-streaming-engine.zip' | sha256sum -c -
$url = "https://ratatoskr.space/pkg/ruview/v0.3.0-streaming-engine.zip"
$out = "v0.3.0-streaming-engine.zip"
Invoke-WebRequest -Uri $url -OutFile $out
if ((Get-FileHash $out -Algorithm SHA256).Hash.ToLowerInvariant() -ne "cc3c0158279774cc53b2a274351eafab500dbf5e00a8f45d9a286417d0ac7d47") { throw "sha256 mismatch" }
curl -fL -o v0.3.0-streaming-engine.tar.gz https://ratatoskr.space/pkg/ruview/v0.3.0-streaming-engine.tar.gz
printf '%s %s\n' '7b891cb38c1382a51772ad9abb755700df0f2cd3bc369fe95e6f8495800338c4' 'v0.3.0-streaming-engine.tar.gz' | sha256sum -c -
$url = "https://ratatoskr.space/pkg/ruview/v0.3.0-streaming-engine.tar.gz"
$out = "v0.3.0-streaming-engine.tar.gz"
Invoke-WebRequest -Uri $url -OutFile $out
if ((Get-FileHash $out -Algorithm SHA256).Hash.ToLowerInvariant() -ne "7b891cb38c1382a51772ad9abb755700df0f2cd3bc369fe95e6f8495800338c4") { throw "sha256 mismatch" }
download via yggdrasil mesh
curl -fL -o v0.3.0-streaming-engine.zip http://14cc7d57b5e70f679b851fe5b272ce17c70632ff4beb5b35ab64bc706b2485af.pk.ygg/pkg/ruview/v0.3.0-streaming-engine.zip
printf '%s %s\n' 'cc3c0158279774cc53b2a274351eafab500dbf5e00a8f45d9a286417d0ac7d47' 'v0.3.0-streaming-engine.zip' | sha256sum -c -
$url = "http://14cc7d57b5e70f679b851fe5b272ce17c70632ff4beb5b35ab64bc706b2485af.pk.ygg/pkg/ruview/v0.3.0-streaming-engine.zip"
$out = "v0.3.0-streaming-engine.zip"
Invoke-WebRequest -Uri $url -OutFile $out
if ((Get-FileHash $out -Algorithm SHA256).Hash.ToLowerInvariant() -ne "cc3c0158279774cc53b2a274351eafab500dbf5e00a8f45d9a286417d0ac7d47") { throw "sha256 mismatch" }
curl -fL -o v0.3.0-streaming-engine.tar.gz http://14cc7d57b5e70f679b851fe5b272ce17c70632ff4beb5b35ab64bc706b2485af.pk.ygg/pkg/ruview/v0.3.0-streaming-engine.tar.gz
printf '%s %s\n' '7b891cb38c1382a51772ad9abb755700df0f2cd3bc369fe95e6f8495800338c4' 'v0.3.0-streaming-engine.tar.gz' | sha256sum -c -
$url = "http://14cc7d57b5e70f679b851fe5b272ce17c70632ff4beb5b35ab64bc706b2485af.pk.ygg/pkg/ruview/v0.3.0-streaming-engine.tar.gz"
$out = "v0.3.0-streaming-engine.tar.gz"
Invoke-WebRequest -Uri $url -OutFile $out
if ((Get-FileHash $out -Algorithm SHA256).Hash.ToLowerInvariant() -ne "7b891cb38c1382a51772ad9abb755700df0f2cd3bc369fe95e6f8495800338c4") { throw "sha256 mismatch" }
| artifact | format | size | hashes |
|---|---|---|---|
| v0.3.0-streaming-engine.zip | zip | 60.8 MiB |
blake3-24 aff182c0ce6e1632a2189ccb3077b5a14a6e3a80c7a6cbdd
sha256 cc3c0158279774cc53b2a274351eafab500dbf5e00a8f45d9a286417d0ac7d47
sha1 9006c6302edb19782c7f77ff60e0437053746e46
|
| v0.3.0-streaming-engine.tar.gz | tar.gz | 59.0 MiB |
blake3-24 f2f177420025e8af6190ae3a1a2da8393adfaa3721905f43
sha256 7b891cb38c1382a51772ad9abb755700df0f2cd3bc369fe95e6f8495800338c4
sha1 131d01fad1863037627cfccccea31a863facf8e9
|
install
http_archive(
name = "ruview",
urls = ["https://ratatoskr.space/pkg/ruview/v0.3.0-streaming-engine.tar.gz"],
integrity = "sha256-e4kcs4wTgqUXcq2au3VXAN8PLNO8Np/pXm+ElYADOMQ=",
strip_prefix = "ruview-v0.3.0-streaming-engine",
)
.url = "https://ratatoskr.space/pkg/ruview/v0.3.0-streaming-engine.tar.gz",
install via yggdrasil mesh
http_archive(
name = "ruview",
urls = ["http://14cc7d57b5e70f679b851fe5b272ce17c70632ff4beb5b35ab64bc706b2485af.pk.ygg/pkg/ruview/v0.3.0-streaming-engine.tar.gz"],
integrity = "sha256-e4kcs4wTgqUXcq2au3VXAN8PLNO8Np/pXm+ElYADOMQ=",
strip_prefix = "ruview-v0.3.0-streaming-engine",
)
.url = "http://14cc7d57b5e70f679b851fe5b272ce17c70632ff4beb5b35ab64bc706b2485af.pk.ygg/pkg/ruview/v0.3.0-streaming-engine.tar.gz",