# Domain Models

This folder contains Domain-Driven Design (DDD) specifications for each major subsystem in RuView.

DDD organizes the codebase around the problem being solved — not around technical layers. Each *bounded context* owns its own data, rules, and language. Contexts communicate through domain events, not by sharing mutable state. This makes the system easier to reason about, test, and extend — whether you're a person or an AI agent.

## Models

| Model | What it covers | Bounded Contexts |
|-------|---------------|------------------|
| [RuvSense](ruvsense-domain-model.md) | Multistatic WiFi sensing, pose tracking, vital signs, edge intelligence | 7 contexts: Sensing, Coherence, Tracking, Field Model, Longitudinal, Spatial Identity, Edge Intelligence |
| [Signal Processing](signal-processing-domain-model.md) | SOTA signal processing: phase cleaning, feature extraction, motion analysis | 3 contexts: CSI Preprocessing, Feature Extraction, Motion Analysis |
| [Training Pipeline](training-pipeline-domain-model.md) | ML training: datasets, model architecture, embeddings, domain generalization | 4 contexts: Dataset Management, Model Architecture, Training Orchestration, Embedding & Transfer |
| [Hardware Platform](hardware-platform-domain-model.md) | ESP32 firmware, edge intelligence, WASM runtime, aggregation, provisioning | 5 contexts: Sensor Node, Edge Processing, WASM Runtime, Aggregation, Provisioning |
| [Sensing Server](sensing-server-domain-model.md) | Single-binary Axum server: CSI ingestion, model management, recording, training, visualization | 5 contexts: CSI Ingestion, Model Management, CSI Recording, Training Pipeline, Visualization |
| [WiFi-Mat](wifi-mat-domain-model.md) | Disaster response: survivor detection, START triage, mass casualty assessment | 3 contexts: Detection, Localization, Alerting |
| [CHCI](chci-domain-model.md) | Coherent Human Channel Imaging: sub-millimeter body surface reconstruction | 3 contexts: Sounding, Channel Estimation, Imaging |
| [rvCSI](rvcsi-domain-model.md) | Edge RF sensing runtime: multi-source CSI ingestion, validation, normalization, event extraction, RuVector RF memory, agent/MCP integration | 7 contexts: Capture, Validation, Signal, Calibration, Event, Memory, Agent |

## How to read these

Each model defines:

- **Ubiquitous Language** — Terms with precise meanings used in both code and conversation
- **Bounded Contexts** — Independent subsystems with clear responsibilities and boundaries
- **Aggregates** — Clusters of objects that enforce business rules (e.g., a PoseTrack owns its keypoints)
- **Value Objects** — Immutable data with meaning (e.g., a CoherenceScore is not just a float)
- **Domain Events** — Things that happened that other contexts may care about
- **Invariants** — Rules that must always be true (e.g., "drift alert requires >2sigma for >3 days")
- **Anti-Corruption Layers** — Adapters that translate between contexts without leaking internals

## Related

- [Architecture Decision Records](../adr/README.md) — Why each technical choice was made
- [User Guide](../user-guide.md) — Setup and API reference
