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Ruview/docs/ddd/README.md
ruv 8658cc3de0 docs: improve RuvSense domain model and add DDD index 
- Add intro explaining DDD purpose and bounded context overview table
- Add Edge Intelligence bounded context (#7) for on-device sensing
- Add ubiquitous language terms: Edge Tier, WASM Module
- Fix frame rate 20 Hz -> 28 Hz (measured on hardware)
- Link each context to its source files and ADRs
- Add NVS configuration table and invariants for edge processing
- Create docs/ddd/README.md introducing all 3 domain models
- Update main README docs table to link to DDD index

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-03-03 17:02:39 -05:00

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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 Multistatic WiFi sensing, pose tracking, vital signs, edge intelligence 7 contexts: Sensing, Coherence, Tracking, Field Model, Longitudinal, Spatial Identity, Edge Intelligence
WiFi-Mat Disaster response: survivor detection, START triage, mass casualty assessment Scan Zone, Survivor Tracking, Triage
CHCI Coherent Human Channel Imaging: sub-millimeter body surface reconstruction Sounding, Channel Estimation, Imaging

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

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