Files
ruv 34eced880f cog-ha-matter (ADR-116 P4): MdnsService -> mdns-sd ServiceInfo bridge
Pure conversion from our wire-format `MdnsService` to the
`mdns_sd::ServiceInfo` shape the responder daemon consumes. No
socket binding, no daemon registration yet — that lands next iter
as a `runtime::spawn_mdns_responder(info)` JoinHandle returning
helper, same shape as `runtime::spawn_publisher`.

  * `MdnsService::to_service_info(hostname, ipv4) ->
        Result<ServiceInfo, mdns_sd::Error>`
  * `mdns-sd = "0.11"` added — aligned with the workspace pin from
    wifi-densepose-desktop so the lockfile doesn't fork dalek-like
    surfaces.

3 new tests:

  * to_service_info_carries_service_type_and_port — locks that
    `_ruview-ha._tcp` (with or without mdns-sd's trailing-dot
    normalisation) and the control port round-trip through the
    conversion
  * to_service_info_propagates_txt_records — every locked TXT
    key from iter 4 (cog_id, mqtt_port, privacy, proto, node_id,
    cog_version) reachable via `get_property_val_str` on the
    converted ServiceInfo
  * to_service_info_does_not_silently_drop_caller_hostname —
    locks the caller-side responsibility for the .local. suffix.
    mdns-sd 0.11 accepts bare hostnames (verified empirically by
    initial test expecting it to reject — it didn't), so the
    wrapper layer must do the trailing-dot dance. Documenting
    that via a named test catches future bumps where the lib
    starts mutating the value.

63/63 cog tests green (60 → 63).

ADR-116 P4 now ⁶⁄₇:  mDNS record-builder,  chain,  JSONL, 
file persistence,  Ed25519 signing,  ServiceInfo conversion;
 daemon register + embedded broker.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-05-23 18:28:10 -04:00
..

Architecture Decision Records

This folder contains 44 Architecture Decision Records (ADRs) that document every significant technical choice in the RuView / WiFi-DensePose project.

Why ADRs?

Building a system that turns WiFi signals into human pose estimation involves hundreds of non-obvious decisions: which signal processing algorithms to use, how to bridge ESP32 firmware to a Rust pipeline, whether to run inference on-device or on a server, how to handle multi-person separation with limited subcarriers.

ADRs capture the context, options considered, decision made, and consequences for each of these choices. They serve three purposes:

  1. Institutional memory — Six months from now, anyone (human or AI) can read why we chose IIR bandpass filters over FIR for vital sign extraction, not just see the code.

  2. AI-assisted development — When an AI agent works on this codebase, ADRs give it the constraints and rationale it needs to make changes that align with the existing architecture. Without them, AI-generated code tends to drift — reinventing patterns that already exist, contradicting earlier decisions, or optimizing for the wrong tradeoffs.

  3. Review checkpoints — Each ADR is a reviewable artifact. When a proposed change touches the architecture, the ADR forces the author to articulate tradeoffs before writing code, not after.

ADRs and Domain-Driven Design

The project uses Domain-Driven Design (DDD) to organize code into bounded contexts — each with its own language, types, and responsibilities. ADRs and DDD work together:

  • ADRs define boundaries: ADR-029 (RuvSense) established multistatic sensing as a separate bounded context from single-node CSI. ADR-042 (CHCI) defined a new aggregate root for coherent channel imaging.
  • DDD models define the language: The RuvSense domain model defines terms like "coherence gate", "dwell time", and "TDM slot" that ADRs reference precisely.
  • Together they prevent drift: An AI agent reading ADR-039 knows that edge processing tiers are configured via NVS keys, not compile-time flags — because the ADR says so. The DDD model tells it which aggregate owns that configuration.

How ADRs are structured

Each ADR follows a consistent format:

  • Context — What problem or gap prompted this decision
  • Decision — What we chose to do and how
  • Consequences — What improved, what got harder, and what risks remain
  • References — Related ADRs, papers, and code paths

Statuses: Proposed (under discussion), Accepted (approved and/or implemented), Superseded (replaced by a later ADR).


ADR Index

Hardware and firmware

ADR Title Status
ADR-012 ESP32 CSI Sensor Mesh for Distributed Sensing Accepted (partial)
ADR-018 ESP32 Development Implementation Path Proposed
ADR-028 ESP32 Capability Audit and Witness Record Accepted
ADR-029 RuvSense Multistatic Sensing Mode (TDM, channel hopping) Proposed
ADR-032 Multistatic Mesh Security Hardening Accepted
ADR-039 ESP32-S3 Edge Intelligence Pipeline (on-device vitals) Accepted (hardware-validated)
ADR-040 WASM Programmable Sensing (Tier 3) Accepted
ADR-041 WASM Module Collection (65 edge modules) Accepted (hardware-validated)
ADR-044 Provisioning Tool Enhancements Proposed
ADR-110 ESP32-C6 firmware extension — Wi-Fi 6 / 802.15.4 / TWT / LP-core Accepted, P1-P10 complete, firmware-side substrate closed at v0.7.0-esp32. Companion docs: WITNESS-LOG-110 (13 §A0.x entries · 99.56 % cross-board RX · 104.1 µs smoothed sync stdev · ≤100 µs target met), ADR-110-REVIEW-GUIDE (one-page reviewer tour), ADR-110-BRANCH-STATE (coordination map vs feat/adr-115-ha-mqtt-matter). Host decoders + tests: Python SyncPacketParser (10) + Rust wifi_densepose_hardware::SyncPacket (15), cross-language hex pin gates drift.

Signal processing and sensing

ADR Title Status
ADR-013 Feature-Level Sensing on Commodity Gear Accepted
ADR-014 SOTA Signal Processing Algorithms Accepted
ADR-021 Vital Sign Detection (breathing, heart rate) Partial
ADR-030 Persistent Field Model and Drift Detection Proposed
ADR-033 CRV Signal Line Sensing Integration Proposed
ADR-037 Multi-Person Pose Detection from Single ESP32 Proposed
ADR-042 Coherent Human Channel Imaging (beyond CSI) Proposed

Machine learning and training

ADR Title Status
ADR-005 SONA Self-Learning for Pose Estimation Partial
ADR-006 GNN-Enhanced CSI Pattern Recognition Partial
ADR-015 Public Dataset Strategy (MM-Fi, Wi-Pose) Accepted
ADR-016 RuVector Training Pipeline Integration Accepted
ADR-017 RuVector Signal + MAT Integration Proposed
ADR-020 Migrate AI Inference to Rust (ONNX Runtime) Accepted
ADR-023 Trained DensePose Model with RuVector Pipeline Proposed
ADR-024 Project AETHER: Contrastive CSI Embeddings Required
ADR-027 Project MERIDIAN: Cross-Environment Generalization Proposed

Platform and UI

ADR Title Status
ADR-019 Sensing-Only UI with Gaussian Splats Accepted
ADR-022 Windows WiFi Enhanced Fidelity (multi-BSSID) Partial
ADR-025 macOS CoreWLAN WiFi Sensing Proposed
ADR-031 RuView Sensing-First RF Mode Proposed
ADR-034 Expo React Native Mobile App Accepted
ADR-035 Live Sensing UI Accuracy and Data Transparency Accepted
ADR-036 Training Pipeline UI Integration Proposed
ADR-043 Sensing Server UI API Completion (14 endpoints) Accepted
ADR-115 Home Assistant integration via MQTT auto-discovery + Matter bridge (HA-DISCO + HA-FABRIC + HA-MIND) Accepted (MQTT track) / Proposed (Matter SDK P8b)

Architecture and infrastructure

ADR Title Status
ADR-001 WiFi-Mat Disaster Detection Architecture Accepted
ADR-002 RuVector RVF Integration Strategy Superseded
ADR-003 RVF Cognitive Containers for CSI Proposed
ADR-004 HNSW Vector Search for Fingerprinting Partial
ADR-007 Post-Quantum Cryptography for Sensing Proposed
ADR-008 Distributed Consensus for Multi-AP Proposed
ADR-009 RVF WASM Runtime for Edge Deployment Proposed
ADR-010 Witness Chains for Audit Trail Integrity Proposed
ADR-011 Proof-of-Reality and Mock Elimination Proposed
ADR-026 Survivor Track Lifecycle (MAT crate) Accepted
ADR-038 Sublinear GOAP for Roadmap Optimization Proposed
ADR-095 rvCSI — Edge RF Sensing Runtime Platform Proposed
ADR-096 rvCSI — Crate Topology, the napi-c Shim, and the napi-rs Node Surface Proposed
ADR-097 Adopt rvCSI as RuView's primary CSI runtime (phased adoption) Proposed
ADR-098 Evaluate ruvnet/midstream for RuView's CSI / WebSocket / mesh pipeline Rejected
ADR-099 Adopt midstream as RuView's real-time introspection + low-latency tap Proposed

  • DDD Domain Models — Bounded context definitions, aggregate roots, and ubiquitous language
  • User Guide — Setup, API reference, and hardware instructions
  • Build Guide — Building from source