ruvnet--ruview/docs/RELEASE-streaming-engine-v0.3.0.md

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-core and wifi-densepose-bfld build #![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.