docs: add RuvSense persistent field model, exotic tiers, and appliance categories
Expands the RuvSense architecture from pose estimation to spatial intelligence platform with persistent electromagnetic world model. Research (Part II added): - 7 exotic capability tiers: field normal modes, RF tomography, intention lead signals, longitudinal biomechanics drift, cross-room continuity, invisible interaction layer, adversarial detection - Signals-not-diagnoses framework with 3 monitoring levels - 5 appliance product categories: Invisible Guardian, Spatial Digital Twin, Collective Behavior Engine, RF Interaction Surface, Pre-Incident Drift Monitor - Regulatory classification (consumer wellness → clinical decision support) - Extended acceptance tests: 7-day autonomous, 30-day appliance validation ADR-030 (new): - Persistent field model architecture with room eigenstructure - Longitudinal drift detection via Welford statistics + HNSW memory - All 5 ruvector crates mapped across 7 exotic tiers - GOAP implementation priority: field modes → drift → tomography → intent - Invisible Guardian recommended as first hardware SKU vertical DDD model (extended): - 3 new bounded contexts: Field Model, Longitudinal Monitoring, Spatial Identity - Full aggregate roots, value objects, domain events for each context - Extended context map showing all 6 bounded contexts - Repository interfaces for field baselines, personal baselines, transitions - Invariants enforcing signals-not-diagnoses boundary https://claude.ai/code/session_01QTX772SDsGVSPnaphoNgNY
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Claude
@@ -591,3 +591,437 @@ pub trait MeshRepository {
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- Re-ID window: Lost tracks eligible for re-identification for 5 seconds
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- Embedding EMA decay: 0.95 (slow adaptation preserves identity across environmental changes)
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- Joint assignment cost must use both position (60%) and embedding (40%) terms
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---
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## Part II: Persistent Field Model Bounded Contexts (ADR-030)
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### Ubiquitous Language (Extended)
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| Term | Definition |
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|------|------------|
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| **Field Normal Mode** | The room's electromagnetic eigenstructure — stable propagation baseline when unoccupied |
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| **Body Perturbation** | Structured change to field caused by a person, after environmental drift is removed |
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| **Environmental Mode** | Principal component of baseline variation due to temperature, humidity, time-of-day |
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| **Personal Baseline** | Per-person rolling statistical profile of biophysical proxies over days/weeks |
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| **Drift Event** | Statistically significant deviation from personal baseline (>2sigma for >3 days) |
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| **Drift Report** | Traceable evidence package: z-score, direction, window, supporting embeddings |
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| **Risk Signal** | Actionable observation about biophysical change — not a diagnosis |
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| **Intention Lead Signal** | Pre-movement dynamics (lean, weight shift) detected 200-500ms before visible motion |
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| **Occupancy Volume** | Low-resolution 3D probabilistic density field from RF tomography |
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| **Room Fingerprint** | HNSW-indexed embedding characterizing a room's electromagnetic identity |
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| **Transition Event** | Person exiting one room and entering another, matched by embedding similarity |
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---
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### 4. Field Model Context
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**Responsibility:** Learn and maintain the room's electromagnetic baseline. Decompose all CSI observations into environmental drift, body perturbation, and anomalies. Provide the foundation for all downstream exotic capabilities.
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```
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┌──────────────────────────────────────────────────────────┐
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│ Field Model Context │
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├──────────────────────────────────────────────────────────┤
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│ │
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│ ┌───────────────┐ ┌───────────────┐ │
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│ │ Calibration │ │ Mode │ │
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│ │ Collector │ │ Extractor │ │
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│ │ (empty-room │ │ (SVD on │ │
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│ │ CSI frames) │ │ baseline) │ │
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│ └───────┬───────┘ └───────┬───────┘ │
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│ │ │ │
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│ └────────┬───────────┘ │
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│ ▼ │
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│ ┌────────────────┐ │
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│ │ Perturbation │ │
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│ │ Extractor │ │
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│ │ (subtract │ │
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│ │ baseline + │──▶ BodyPerturbation │
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│ │ project out │ │
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│ │ env modes) │ │
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│ └────────┬───────┘ │
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│ │ │
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│ ┌────────▼───────┐ │
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│ │ RF Tomographer│ │
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│ │ (sparse 3D │──▶ OccupancyVolume │
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│ │ inversion) │ │
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│ └────────────────┘ │
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│ │
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└──────────────────────────────────────────────────────────┘
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```
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**Aggregates:**
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- `FieldNormalMode` (Aggregate Root)
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**Value Objects:**
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- `BodyPerturbation` — Per-link CSI residual after baseline + environmental mode removal
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- `EnvironmentalMode` — One principal component of baseline variation
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- `OccupancyVolume` — 3D voxel grid of estimated mass density
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- `CalibrationStatus` — Fresh / Stale / Expired (based on time since last empty-room)
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**Domain Services:**
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- `CalibrationService` — Detects empty-room windows, collects calibration data
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- `ModeExtractionService` — SVD computation for environmental modes
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- `PerturbationService` — Baseline subtraction + mode projection
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- `TomographyService` — Sparse L1 inversion for occupancy volume
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**RuVector Integration:**
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- `ruvector-solver` → SVD for mode extraction; L1 for tomographic inversion
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- `ruvector-temporal-tensor` → Baseline history compression
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- `ruvector-attn-mincut` → Mode-subcarrier assignment partitioning
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---
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### 5. Longitudinal Monitoring Context
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**Responsibility:** Maintain per-person biophysical baselines over days/weeks. Detect meaningful drift. Produce traceable evidence reports. Enforce the signals-not-diagnoses boundary.
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```
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┌──────────────────────────────────────────────────────────┐
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│ Longitudinal Monitoring Context │
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├──────────────────────────────────────────────────────────┤
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│ │
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│ ┌───────────────┐ ┌───────────────┐ │
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│ │ Metric │ │ Baseline │ │
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│ │ Extractor │ │ Updater │ │
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│ │ (pose → gait,│ │ (Welford │ │
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│ │ stability, │ │ online │ │
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│ │ breathing) │ │ statistics) │ │
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│ └───────┬───────┘ └───────┬───────┘ │
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│ │ │ │
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│ └────────┬───────────┘ │
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│ ▼ │
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│ ┌────────────────┐ │
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│ │ Drift Detector│ │
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│ │ (z-score vs │ │
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│ │ personal │ │
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│ │ baseline) │ │
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│ └────────┬───────┘ │
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│ ▼ │
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│ ┌────────────────┐ │
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│ │ Evidence │ │
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│ │ Assembler │──▶ DriftReport │
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│ │ (embeddings + │ │
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│ │ timestamps + │ │
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│ │ graph links) │ │
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│ └────────────────┘ │
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│ │
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└──────────────────────────────────────────────────────────┘
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```
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**Aggregates:**
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- `PersonalBaseline` (Aggregate Root)
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**Entities:**
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- `DailyMetricSummary` — One day's worth of compressed metric statistics per person
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**Value Objects:**
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- `DriftReport` — Evidence package with z-score, direction, window, embeddings
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- `DriftMetric` — GaitSymmetry / StabilityIndex / BreathingRegularity / MicroTremor / ActivityLevel
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- `DriftDirection` — Increasing / Decreasing
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- `MonitoringLevel` — Physiological (Level 1) / Drift (Level 2) / RiskCorrelation (Level 3)
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- `WelfordStats` — Online mean/variance accumulator (count, mean, M2)
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**Domain Services:**
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- `MetricExtractionService` — Extract biomechanical proxies from pose tracks
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- `BaselineUpdateService` — Update Welford statistics with daily observations
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- `DriftDetectionService` — Compute z-scores, identify significant deviations
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- `EvidenceAssemblyService` — Package supporting embeddings and graph constraints
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**RuVector Integration:**
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- `ruvector-temporal-tensor` → Compressed daily summary storage
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- `ruvector-attention` → Weight metric significance in drift score
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- `ruvector-mincut` → Temporal changepoint detection in metric series
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- HNSW → Similarity search across longitudinal embedding record
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**Invariants:**
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- Baseline requires 7+ observation days before drift detection activates
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- Drift alert requires >2sigma deviation sustained for >3 consecutive days
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- Evidence chain must include start/end embeddings bracketing the drift window
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- System never outputs diagnostic language — only metric values and deviations
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- Personal baseline decay: Welford stats use full history (no windowing) for stability
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---
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### 6. Spatial Identity Context
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**Responsibility:** Maintain cross-room identity continuity via environment fingerprinting and transition graphs. Track who is where across spaces without storing images.
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```
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┌──────────────────────────────────────────────────────────┐
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│ Spatial Identity Context │
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├──────────────────────────────────────────────────────────┤
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│ │
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│ ┌───────────────┐ ┌───────────────┐ │
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│ │ Room │ │ Transition │ │
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│ │ Fingerprint │ │ Detector │ │
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│ │ Index (HNSW) │ │ (exit/entry │ │
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│ └───────┬───────┘ │ events) │ │
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│ │ └───────┬───────┘ │
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│ │ │ │
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│ └────────┬───────────┘ │
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│ ▼ │
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│ ┌────────────────┐ │
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│ │ Cross-Room │ │
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│ │ Matcher │ │
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│ │ (exit embed ↔ │──▶ TransitionEvent │
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│ │ entry embed) │ │
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│ └────────┬───────┘ │
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│ │ │
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│ ┌────────▼───────┐ │
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│ │ Transition │ │
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│ │ Graph │ │
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│ │ (rooms, │ │
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│ │ persons, │ │
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│ │ timestamps) │ │
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│ └────────────────┘ │
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│ │
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└──────────────────────────────────────────────────────────┘
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```
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**Aggregates:**
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- `SpatialIdentityGraph` (Aggregate Root)
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**Entities:**
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- `RoomProfile` — HNSW-indexed electromagnetic fingerprint of a room
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- `PersonSpatialRecord` — Which rooms a person has visited, in order
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**Value Objects:**
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- `TransitionEvent` — Person, from_room, to_room, timestamps, embedding similarity
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- `RoomFingerprint` — 128-dim AETHER embedding of the room's CSI profile
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- `SpatialContinuity` — Confidence score for cross-room identity chain
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**Domain Services:**
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- `RoomFingerprintService` — Compute and index room electromagnetic profiles
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- `TransitionDetectionService` — Detect exits (track lost near boundary) and entries (new track)
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- `CrossRoomMatchingService` — HNSW similarity between exit and entry embeddings
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- `TransitionGraphService` — Build and query the room-person-time graph
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**RuVector Integration:**
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- HNSW → Room and person fingerprint similarity search
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- `ruvector-mincut` → Transition graph partitioning for occupancy analysis
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**Invariants:**
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- Cross-room match requires >0.80 cosine similarity AND <60s temporal gap
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- Room fingerprint must be recalculated if mesh topology changes
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- Transition graph edges are immutable once created (append-only audit trail)
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- No image data stored — only 128-dim embeddings and structural events
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---
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### Domain Events (Extended)
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#### Field Model Events
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```rust
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pub enum FieldModelEvent {
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/// Baseline calibration completed (empty room detected and measured)
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BaselineCalibrated {
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room_id: RoomId,
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n_modes: usize,
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variance_explained: f32, // fraction of total variance captured
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timestamp_us: u64,
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},
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/// Environmental drift detected (baseline shift without body cause)
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EnvironmentalDriftDetected {
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room_id: RoomId,
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magnitude: f32,
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drift_type: DriftProfile,
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timestamp_us: u64,
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},
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/// Anomalous perturbation detected (does not match body or environment)
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AnomalousPerturbation {
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room_id: RoomId,
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anomaly_score: f32,
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affected_links: Vec<usize>,
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timestamp_us: u64,
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},
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/// Occupancy volume updated
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OccupancyUpdated {
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room_id: RoomId,
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occupied_voxels: usize,
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total_voxels: usize,
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timestamp_us: u64,
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},
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}
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```
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#### Longitudinal Monitoring Events
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```rust
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pub enum LongitudinalEvent {
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/// Personal baseline established (7-day calibration complete)
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BaselineEstablished {
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person_id: PersonId,
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observation_days: u32,
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metrics_tracked: Vec<DriftMetric>,
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timestamp_us: u64,
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},
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/// Drift detected — biophysical metric significantly changed
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DriftDetected {
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person_id: PersonId,
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report: DriftReport,
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timestamp_us: u64,
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},
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/// Drift resolved — metric returned to baseline range
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DriftResolved {
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person_id: PersonId,
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metric: DriftMetric,
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resolution_days: u32,
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timestamp_us: u64,
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},
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/// Daily summary computed for a person
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DailySummaryComputed {
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person_id: PersonId,
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date: u64, // day timestamp
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metrics: Vec<(DriftMetric, f32)>, // metric, today's value
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timestamp_us: u64,
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},
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}
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```
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#### Spatial Identity Events
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```rust
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pub enum SpatialEvent {
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/// New room fingerprinted
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RoomFingerprinted {
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room_id: RoomId,
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fingerprint_dims: usize,
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timestamp_us: u64,
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},
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/// Person transitioned between rooms
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PersonTransitioned {
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person_id: PersonId,
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from_room: RoomId,
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to_room: RoomId,
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similarity: f32,
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gap_duration_ms: u64,
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timestamp_us: u64,
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},
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/// Cross-room match failed (new person in destination room)
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CrossRoomMatchFailed {
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entry_room: RoomId,
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entry_embedding: Vec<f32>,
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candidates_checked: usize,
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best_similarity: f32,
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timestamp_us: u64,
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},
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}
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```
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---
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### Extended Context Map
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```
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┌──────────────────────────────────────────────────────────────────────┐
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│ RuvSense Full System (ADR-029 + ADR-030) │
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├──────────────────────────────────────────────────────────────────────┤
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│ │
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│ ┌───────────────┐ FusedFrame ┌──────────────┐ │
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│ │ Multistatic │────────────▶│ Pose Tracking │ │
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│ │ Sensing │ │ Context │ │
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│ └───────┬───────┘ └───────┬───────┘ │
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│ │ │ │
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│ │ │ TrackedPose │
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│ │ │ │
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│ ▼ ┌───────▼───────┐ │
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│ ┌───────────────┐ │ Longitudinal │ │
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│ │ Coherence │ │ Monitoring │ │
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│ │ Context │ │ Context │ │
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│ └───────┬───────┘ └───────┬───────┘ │
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│ │ Gates │ DriftReport │
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│ │ │ │
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│ ▼ ▼ │
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│ ┌───────────────┐ ┌───────────────┐ │
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│ │ Field Model │ │ Spatial │ │
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│ │ Context │ │ Identity │ │
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│ │ (baseline, │ │ Context │ │
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│ │ modes, │ │ (cross-room, │ │
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│ │ tomography) │ │ transitions)│ │
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│ └───────────────┘ └───────────────┘ │
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│ │
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│ ──────────────── Event Bus ────────────────── │
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│ SensingEvent | CoherenceEvent | TrackingEvent | │
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│ FieldModelEvent | LongitudinalEvent | SpatialEvent │
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│ │
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├──────────────────────────────────────────────────────────────────────┤
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│ UPSTREAM: wifi-densepose-{hardware, nn, signal} │
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│ SIBLINGS: AETHER (embeddings) | MERIDIAN (geometry) | MAT (triage) │
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└──────────────────────────────────────────────────────────────────────┘
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```
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**New Relationship Types:**
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- Multistatic Sensing → Field Model: **Partnership** (sensing provides raw CSI; field model provides perturbation extraction)
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- Pose Tracking → Longitudinal Monitoring: **Customer/Supplier** (tracking provides daily pose metrics; monitoring builds baselines)
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- Pose Tracking → Spatial Identity: **Customer/Supplier** (tracking provides track exit/entry events; spatial maintains transition graph)
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- Coherence → Field Model: **Subscriber** (coherence events inform baseline recalibration)
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- Longitudinal Monitoring → Spatial Identity: **Partnership** (person profiles shared for cross-room matching)
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---
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### Extended Repository Interfaces
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```rust
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/// Persists field normal modes and calibration history
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pub trait FieldModelRepository {
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fn save_baseline(&self, room_id: RoomId, mode: &FieldNormalMode);
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fn load_baseline(&self, room_id: RoomId) -> Option<FieldNormalMode>;
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fn list_rooms(&self) -> Vec<RoomId>;
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fn save_occupancy_snapshot(&self, room_id: RoomId, volume: &OccupancyVolume, timestamp_us: u64);
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}
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/// Persists personal baselines and drift history
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pub trait LongitudinalRepository {
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fn save_baseline(&self, baseline: &PersonalBaseline);
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fn load_baseline(&self, person_id: &PersonId) -> Option<PersonalBaseline>;
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fn save_daily_summary(&self, person_id: &PersonId, summary: &DailyMetricSummary);
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fn load_summaries(&self, person_id: &PersonId, days: u32) -> Vec<DailyMetricSummary>;
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fn save_drift_report(&self, report: &DriftReport);
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fn load_drift_history(&self, person_id: &PersonId) -> Vec<DriftReport>;
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}
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/// Persists room fingerprints and transition graphs
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pub trait SpatialIdentityRepository {
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fn save_room_fingerprint(&self, room_id: RoomId, fingerprint: &RoomFingerprint);
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fn load_room_fingerprint(&self, room_id: RoomId) -> Option<RoomFingerprint>;
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fn save_transition(&self, transition: &TransitionEvent);
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fn load_transitions(&self, person_id: &PersonId, window_ms: u64) -> Vec<TransitionEvent>;
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fn load_room_occupancy(&self, room_id: RoomId) -> Vec<PersonId>;
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}
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```
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---
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### Extended Invariants
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|
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#### Field Model
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- Baseline calibration requires ≥10 minutes of empty-room CSI (≥12,000 frames at 20 Hz)
|
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- Environmental modes capped at K=5 (more modes overfit to noise)
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- Tomographic inversion only valid with ≥8 links (4 nodes minimum)
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- Baseline expires after 24 hours if not refreshed during quiet period
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- Perturbation energy must be non-negative (enforced by magnitude computation)
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|
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#### Longitudinal Monitoring
|
||||
- Personal baseline requires ≥7 observation days before drift detection activates
|
||||
- Drift alert requires >2sigma deviation sustained for ≥3 consecutive days
|
||||
- Evidence chain must include embedding pairs bracketing the drift window
|
||||
- Output must never use diagnostic language — only metric values and statistical deviations
|
||||
- Daily summaries stored for ≥90 days (rolling retention policy)
|
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- Welford statistics use full history (no windowing) for maximum stability
|
||||
|
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#### Spatial Identity
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||||
- Cross-room match requires >0.80 cosine similarity AND <60s temporal gap
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||||
- Room fingerprint recalculated when mesh topology changes (node added/removed/moved)
|
||||
- Transition graph is append-only (immutable audit trail)
|
||||
- No image data stored — only 128-dim embeddings and structural events
|
||||
- Maximum 100 rooms indexed per deployment (HNSW scaling constraint)
|
||||
|
||||
Reference in New Issue
Block a user