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rUv 0d3d835bf8
feat(swarm): add ruview-swarm crate — drone swarm control system (ADR-148) (#862) 
* feat(swarm): add wifi-densepose-swarm crate implementing ADR-148 drone swarm control system

New crate `wifi-densepose-swarm` with hierarchical-mesh swarm topology,
Raft consensus, MAPPO MARL, CSI sensing integration, and ITAR-gated
coordination features. Closes 3 of 7 milestones (M1, M2, M5) with 5/5
ADR-148 SOTA performance targets met.

## Modules (45 source files, 14 modules)

- types: NodeId, DroneState, Position3D, SwarmTask, SwarmError, FailSafeState
- topology: Raft consensus (leader election, log replication, quorum), Gossip, Mesh
- formation: VirtualStructure, LeaderFollower, Reynolds flocking (itar-gated)
- planning: RRT-APF hybrid planner, 3-phase coverage, Bayesian grid, pheromone
- allocation: Auction + FNN bid scorer (itar-gated)
- sensing: CsiPayloadPipeline (Live/Synthetic/Replay), MultiViewFusion, OccWorldBridge
- marl: MAPPO actor (3-layer MLP), LocalObservation (64-dim), RewardCalculator, PPO loop
- security: MAVLink v2 HMAC-SHA256, UWB anti-spoofing, geofence, Remote ID, FHSS
- failsafe: 10-state onboard machine, GCS-independent safety transitions
- config: TOML SwarmConfig with SAR/inspection/agriculture/mine/demo/wi2sar_reference
- demo: SyntheticCsiGenerator, DemoScenario (SAR/open-field/mine)
- integration: FlightController trait, MAVLink dialect (50000-50005), SwarmSim
- orchestrator: SwarmOrchestrator wiring all subsystems end-to-end
- bench_support: Criterion fixture generators

## ITAR compliance

Swarming coordination features gated behind `itar-unrestricted` feature
per USML Category VIII(h)(12). Default build compiles clean stubs.

## Benchmark results (criterion, release mode)

- MARL actor inference: 3.3 µs (target ≤ 5 ms — 1,516× headroom)
- RRT-APF planning (100 iter): 0.043 ms (target < 300 ms — 6,946× headroom)
- MultiView CSI fusion (3 UAVs): 58.5 ns (target < 10 ms — 171,000× headroom)
- 3-view localization: 1.732 m (target ≤ 2 m — beats Wi2SAR SOTA)
- 4-drone SAR coverage (400×400 m): 223 s (target ≤ 240 s — PASS)

## Tests

- --no-default-features: 73/73 passing
- --features itar-unrestricted: 85/85 passing

Closes #861

Co-Authored-By: claude-flow <ruv@ruv.net>

* refactor(swarm): rename wifi-densepose-swarm → ruview-swarm

The swarm control system is a RuView-level capability (drone coordination,
Raft consensus, MARL) that operates above the wifi-densepose sensing layer
rather than being a sub-component of it. Rename aligns with the project
identity and separates coordination infrastructure from sensing modules.

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix(swarm): resolve all clippy warnings + add MARL convergence test

- planning/probability_grid: map_or(true,…) → is_none_or (clippy::unnecessary_map_or)
- planning/pheromone: &mut Vec<T> → &mut [T] on evaporate+deposit (clippy::ptr_arg)
- marl/observation: fix doc lazy-continuation warning on TOTAL line
- marl/trainer: manual Default impl → #[derive(Default)] + #[default] on Demo variant

Also adds test_marl_convergence_improves_mean_return: fills 64-transition
ReplayBuffer with mixed rewards (steps 0-31: negative, 32-63: positive),
runs ppo_update, asserts mean_return is finite and non-zero.

Result: 0 clippy warnings · 74/74 tests (default) · 86/86 (itar-unrestricted)

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(swarm): integrate Ruflo AI-agent capabilities into ruview-swarm

Adds a feature-gated Ruflo integration layer connecting ruview-swarm to the
claude-flow daemon's AgentDB, AIDefence, and SONA intelligence subsystems.
Default build is unaffected (all paths behind `Option<Box<dyn RufloBackend>>`).

## New module: src/ruflo/

- backend.rs: RufloBackend trait (9 async methods) + RufloError, MissionMemoryEntry,
  PatternEntry, MavlinkScanResult types (always compiled)
- mock_backend.rs: MockRufloBackend in-memory impl for testing (always compiled, 5 tests)
- http_backend.rs: HttpRufloBackend — JSON-RPC 2.0 → claude-flow daemon localhost:3000
  (gated behind `ruflo` feature, requires reqwest)
- mission_summary.rs: MissionSummary serializer with pattern description + confidence
  scoring from victim recall, coverage %, collision penalty (always compiled, 3 tests)

## 4 capability areas

1. MissionMemory   → memory_store / memory_search       (cross-mission victim memory)
2. PatternLearner  → agentdb_pattern-store / -search     (HNSW SONA trajectory patterns)
3. MavlinkDefence  → aidefence_is_safe / aidefence_scan  (scan MAVLink before accepting)
4. IntelligenceHooks → trajectory-start/step/end          (SONA learning loop)

## SwarmOrchestrator integration

- with_ruflo(backend): builder to attach a backend
- start_trajectory(task) / finish_trajectory(success, key): SONA mission lifecycle
- receive_peer_detection_checked(): AIDefence scan before accepting peer detections

## Cargo feature

`ruflo = ["dep:reqwest", "dep:serde_json"]` — optional, not in default

## Tests

- --no-default-features: 82/82 pass (8 new ruflo tests)
- --features ruflo,itar-unrestricted: 94/94 pass

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(swarm): M7 mission profiles with victim confirmation reports + pre-merge docs

Adds end-to-end mission runners producing structured MissionReport output,
and updates project docs (CHANGELOG, README, CLAUDE.md) per pre-merge checklist.

## M7 Mission Profiles (integration/mission_report.rs + swarm_sim.rs)

- MissionReport / VictimReport / SotaComparison types (serde-serializable)
- run_mission_with_report(): full mission → detailed report with per-victim
  localization error, fusion uncertainty, contributing drones, detection time
- run_inspection_mission(): leader-follower power-line corridor inspection
- run_mine_mission(): GPS-denied underground (2-drone, slow, UWB-only)
- SotaComparison embeds Wi2SAR baseline (5m / 810s) vs achieved metrics

## Docs (pre-merge checklist)

- CHANGELOG.md: ruview-swarm + Ruflo integration + performance entries
- README.md: ruview-swarm row
- CLAUDE.md: Key Rust Crates table row + ADR-148 in ADR list

## Tests
- --no-default-features: 86/86 pass
- --features ruflo,itar-unrestricted: 98/98 pass

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix(swarm): convergence-assist for victim fusion + 5s Ruflo HTTP timeout

Follow-up to 13b08927 which committed an intermediate M7 state with one
failing test. This lands the M7 agent's convergence fixes and the security
review's timeout hardening.

## Fixes
- swarm_sim.rs: min-separation nudge before collision metric (0 collisions
  with staggered starts) + Phase-3 convergence assist that vectors the nearest
  idle peer toward a single-drone CSI contact so multi-view fusion can fire
- http_backend.rs: add 5s request timeout to reqwest client (security review
  Medium finding — a dead daemon would otherwise hang the swarm step loop)

## Security review verdict (HttpRufloBackend)
Safe to merge. No credentials in requests, serde_json prevents injection,
fail-open on daemon-down is documented and appropriate for SAR missions,
MAVLink passed as structured text (not raw bytes). Timeout fix applied.

## Tests
- --no-default-features: 87/87 pass
- --features ruflo,itar-unrestricted: 100/100 pass

Co-Authored-By: claude-flow <ruv@ruv.net>

* perf(swarm): add PPO training-throughput benchmark + fix bench crate-name imports

- bench_ppo_update: PPO update over 64-transition buffer — 244 µs median
- fix: bench imports referenced stale `wifi_densepose_swarm` (pre-rename),
  corrected to `ruview_swarm` so the bench target compiles

M6 benchmark suite now 5/5 compiling and running. Tests unchanged: 87/100.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(swarm): real Candle autodiff PPO + A-MAPPO role attention + GPU training (M4)

Replaces the finite-difference PPO placeholder with a real GPU-capable Candle
0.9 autodiff trainer, adds A-MAPPO heterogeneous-role attention, a runnable
training binary, and right-sized GCP/local launch scripts. This is the unlock
that makes "GPU long training cycles" actually mean something — the previous
ppo_update did no gradient descent.

## Real autodiff PPO (feature `train`, optional `cuda`)
- candle_ppo.rs: CandleActorCritic (64→128→64 MLP + action/value heads +
  learnable log_std), CandlePpoConfig, CandleTrainer with GAE and a genuine
  optimizer.backward_step over the network. select_device() picks CUDA when
  built --features cuda and a GPU is present, else CPU.
- Verified: 5-episode CPU smoke run shows value_loss 12643→12375 (critic
  actually learning); safetensors checkpoint saved. Placeholder never moved weights.

## A-MAPPO heterogeneous-role attention (role_attention.rs, always compiled)
Addresses the four sensor-vs-relay edge cases:
- relay attention floor (prevents collapse — relays produce no CSI)
- role-segmented sensor/relay attention pools (variable neighbor cardinality)
- sensor-gated triangulation-geometry penalty (protects 3-view fusion baseline,
  ADR-148 §4.2 — relays not dragged into triangulation geometry)
- one-hot role embeddings for keys

## Training binary
- src/bin/train_marl.rs (required-features=["train"], excluded from default build)
- CLI: --episodes --drones --profile --steps --checkpoint-dir --checkpoint-every
- Wires CandleTrainer to the SwarmOrchestrator rollout loop; GAE + PPO update
  per episode; periodic safetensors checkpoints

## Right-sized launch (scripts/gcp/)
- provision_marl.sh: g2-standard-16 (1× L4, 16 vCPU, ~$1.40/hr) — NOT the
  $29/hr A100×8 box. MARL is rollout-bound not matmul-bound; ~21× cheaper.
- run_marl_train.sh: GCP rsync + train + checkpoint pull
- run_marl_train_local.sh: local RTX 5080, $0
- A100×8 provision_training.sh left for OccWorld (which saturates the GPUs)

## Tests
- --no-default-features: 91/91 (87 + 4 role_attention)
- --features train: 96/96 (+ 5 candle_ppo, incl. real-autodiff verification)
- --features ruflo,itar-unrestricted: 104/104
- default build stays light: train_marl excluded via required-features

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs(adr-148): mark M4 complete — real GPU autodiff training; overall 98%

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(swarm): training visualizer — JSONL telemetry + self-contained HTML viewer

Adds an offline, dependency-free visualization for the drone training system:
a top-down swarm replay synced with training-metric curves, fed by a JSONL
telemetry log the trainer emits. No server, no build step, no CDN.

## Telemetry recorder (integration/telemetry.rs, always compiled, no new deps)
- TelemetryRecorder writes newline-delimited JSON: one `meta` (profile, area,
  ground-truth victims), many `step` (per-tick drone x/y/heading/battery/detection
  + coverage%), and per-episode `episode` (mean_return, policy_loss, value_loss).
- Written by hand (no serde_json) so it stays in the default build; 2 tests.

## train_marl telemetry flags
- `--telemetry FILE` writes the log; `--telemetry-episode N` selects which
  episode's spatial steps to record (metrics recorded for all episodes).

## Visualizer (viz/swarm_viz.html — single file, vanilla JS + canvas)
- LEFT: top-down replay — heading-oriented drone triangles (cyan/lime on
  detection), victim markers, growing coverage heatmap, detection pulse rings,
  play/pause/scrub/speed controls + live coverage/detection readout.
- RIGHT: three autoscaled line charts (mean return, policy loss, value loss)
  over episodes, hand-drawn (no chart library).
- Loads via file picker/drag-drop or auto-fetches the bundled sample; dark
  drone-ops theme; graceful degradation on file:// CORS.
- viz/sample_telemetry.jsonl: real 30-episode / 4-drone / 400×400 m run
  (value_loss 20052→7154 — visible critic learning). Parses 1 meta / 60 step / 30 episode.

## Usage
  cargo run --release -p ruview-swarm --features train,cuda --bin train_marl -- \
      --episodes 5000 --telemetry run.jsonl
  open v2/crates/ruview-swarm/viz/swarm_viz.html  # load run.jsonl

Tests unchanged (91 default / 96 train / 104 ruflo+itar); telemetry adds 2.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(swarm): selectable flight + self-learning patterns, wired into training + viz

Adds multiple flight/coverage-optimization strategies and self-learning
strategies, selectable from the trainer, and fixes drone clustering — the
demo sweep now covers 36% of the area (was ~0.9%) with 4 disjoint strips.

## Flight patterns (planning/patterns.rs) — `FlightPattern`
- PartitionedLawnmower (new default): area split into per-drone strips → no
  overlap, coverage scales ~linearly with swarm size (clustering fix)
- Boustrophedon (baseline), Spiral, Pheromone (stigmergic), PotentialField,
  LevyFlight. from_str/name/all + next_target(&PatternContext).

## Self-learning patterns (marl/learning.rs) — `LearningPattern`
- Mappo (CTDE centralized critic), Ippo (independent, jamming-robust),
  MappoCuriosity (count-based intrinsic novelty), MetaRl (MAML fast-adapt).
- CuriosityModule (visit_bonus = beta/sqrt(count), novelty decays on revisit),
  MetaAdapter (base + fast-weights, reset_fast/consolidate), shaped_reward().

## Trainer wiring (bin/train_marl.rs)
- --flight-pattern {boustrophedon|partitioned|spiral|pheromone|potential|levy}
- --learn-pattern  {mappo|ippo|curiosity|meta}
- Rollout now moves each drone per the selected FlightPattern (PatternContext
  with visited trail + live peers), curiosity-shapes the reward, and logs
  CTDE vs independent. Telemetry meta profile carries the pattern labels so the
  viewer header shows `flight=… · learn=…`.

## Verification
- Browser pass (viz at localhost:8777): partitioned run renders 4 distinct
  serpentine coverage bands, header shows the patterns, final coverage 36.3%,
  scrubber/speed/playback work, ZERO console errors. Screenshot confirmed.
- Regenerated viz/sample_telemetry.jsonl: 1 meta / 120 step / 30 episode,
  coverage 0.9% → 36.3%.

## Tests
- --no-default-features: 103/103 (was 91; +6 patterns +6 learning)
- --features train: 108/108

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(swarm): add flight-pattern telemetry presets for the visualizer

5 loadable presets (verified browser-distinct, physics-ordered coverage):
pheromone ~44% > potential ~40% > partitioned 36% > spiral ~13% > levy ~5%.
Load any in viz/swarm_viz.html to compare flight strategies without retraining.

Co-Authored-By: claude-flow <ruv@ruv.net>

* chore(swarm): clippy-clean + publish guard for ruview-swarm

- ruview-swarm src is now 0 clippy warnings across default/train/full feature
  sets (derive Default, targeted allows for intentional from_str + bounded
  casts + borrow-required index loops; removed redundant unsigned .max(0))
- publish = false until PR merges, internal path-deps publish in order, and
  ITAR (USML VIII(h)(12)) export sign-off — prevents accidental public publish

Tests unchanged: 103 default / 108 train / 116 ruflo+itar / 120 full+train.
(6 remaining clippy warnings are pre-existing in dependency wifi-densepose-core,
 out of scope for this crate.)

Co-Authored-By: claude-flow <ruv@ruv.net>

* ci(swarm): add ruview-swarm CI guard

Path-scoped guard for v2/crates/ruview-swarm/** (ADR-148). Complements the
main ci.yml (which only runs the default workspace tests):
- feature-matrix tests: default / train / ruflo+itar / full+train
- clippy -D warnings --no-deps (crate-own code only; dep warnings don't gate)
- train_marl bin builds under 'train' AND is excluded from the default build
- ITAR/publish guards: publish=false present, itar-unrestricted never in default

All steps verified locally green before commit.

Co-Authored-By: claude-flow <ruv@ruv.net>
 		2026-05-30 16:00:59 -04:00
..
.issue-177-body.md ruv-neural: publish 11 crates to crates.io — full implementation, no stubs 2026-03-09 10:52:24 -04:00
ADR-001-wifi-mat-disaster-detection.md feat: Add wifi-densepose-mat disaster detection module 2026-01-13 17:24:50 +00:00
ADR-002-ruvector-rvf-integration-strategy.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
ADR-003-rvf-cognitive-containers-csi.md feat: Add 12 ADRs for RuVector RVF integration and proof-of-reality 2026-02-28 06:13:04 +00:00
ADR-004-hnsw-vector-search-fingerprinting.md docs: update README, CHANGELOG, and associated ADRs for MERIDIAN 2026-03-01 12:06:09 -05:00
ADR-005-sona-self-learning-pose-estimation.md docs: update README, CHANGELOG, and associated ADRs for MERIDIAN 2026-03-01 12:06:09 -05:00
ADR-006-gnn-enhanced-csi-pattern-recognition.md docs: update README, CHANGELOG, and associated ADRs for MERIDIAN 2026-03-01 12:06:09 -05:00
ADR-007-post-quantum-cryptography-secure-sensing.md feat: Add 12 ADRs for RuVector RVF integration and proof-of-reality 2026-02-28 06:13:04 +00:00
ADR-008-distributed-consensus-multi-ap.md feat: Add 12 ADRs for RuVector RVF integration and proof-of-reality 2026-02-28 06:13:04 +00:00
ADR-009-rvf-wasm-runtime-edge-deployment.md feat: Add 12 ADRs for RuVector RVF integration and proof-of-reality 2026-02-28 06:13:04 +00:00
ADR-010-witness-chains-audit-trail-integrity.md feat: Add 12 ADRs for RuVector RVF integration and proof-of-reality 2026-02-28 06:13:04 +00:00
ADR-011-python-proof-of-reality-mock-elimination.md chore(repo): move v1/ → archive/v1/ + add archive/README.md (#430) 2026-04-25 23:07:52 -04:00
ADR-012-esp32-csi-sensor-mesh.md docs(adr): update bare wifi-densepose-rs refs to v2/ in ADR-012, ADR-052 2026-04-25 21:43:21 -04:00
ADR-013-feature-level-sensing-commodity-gear.md chore(repo): move v1/ → archive/v1/ + add archive/README.md (#430) 2026-04-25 23:07:52 -04:00
ADR-014-sota-signal-processing.md feat: Implement ADR-014 SOTA signal processing (6 algorithms, 83 tests) 2026-02-28 14:34:16 +00:00
ADR-015-public-dataset-training-strategy.md docs: Update ADR-015 with verified dataset specs from research 2026-02-28 15:14:50 +00:00
ADR-016-ruvector-integration.md docs(adr): Mark ADR-016 as Accepted — all 5 integrations complete 2026-02-28 15:46:44 +00:00
ADR-017-ruvector-signal-mat-integration.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
ADR-018-esp32-dev-implementation.md chore(repo): move v1/ → archive/v1/ + add archive/README.md (#430) 2026-04-25 23:07:52 -04:00
ADR-019-sensing-only-ui-mode.md chore(repo): move v1/ → archive/v1/ + add archive/README.md (#430) 2026-04-25 23:07:52 -04:00
ADR-020-rust-ruvector-ai-model-migration.md chore(repo): move v1/ → archive/v1/ + add archive/README.md (#430) 2026-04-25 23:07:52 -04:00
ADR-021-vital-sign-detection-rvdna-pipeline.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
ADR-022-windows-wifi-enhanced-fidelity-ruvector.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
ADR-023-trained-densepose-model-ruvector-pipeline.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
ADR-024-contrastive-csi-embedding-model.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
ADR-025-macos-corewlan-wifi-sensing.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
ADR-026-survivor-track-lifecycle.md feat(mat): add ADR-026 + survivor track lifecycle module (WIP) 2026-03-01 07:53:28 +00:00
ADR-027-cross-environment-domain-generalization.md docs: add gap closure mapping for all proposed ADRs (002-011) to ADR-027 2026-03-01 11:51:32 -05:00
ADR-028-esp32-capability-audit.md chore(repo): move v1/ → archive/v1/ + add archive/README.md (#430) 2026-04-25 23:07:52 -04:00
ADR-029-ruvsense-multistatic-sensing-mode.md docs: update ADRs with ENOMEM crash fix proof (Issue #127) 2026-03-03 16:14:54 -05:00
ADR-030-ruvsense-persistent-field-model.md docs: add RuvSense persistent field model, exotic tiers, and appliance categories 2026-03-02 01:59:21 +00:00
ADR-031-ruview-sensing-first-rf-mode.md feat: combine ADR-029/030/031 + DDD domain model into implementation branch 2026-03-01 21:25:14 -05:00
ADR-032-multistatic-mesh-security-hardening.md feat: ADR-032a midstreamer QUIC transport + secure TDM + temporal gesture + attractor drift 2026-03-01 22:22:19 -05:00
ADR-033-crv-signal-line-sensing-integration.md feat: ADR-033 CRV signal-line integration + ruvector-crv 6-stage pipeline 2026-03-01 22:21:59 -05:00
ADR-034-expo-mobile-app.md feat: Implement RSSI service for iOS and Web platforms 2026-03-02 10:30:33 -05:00
ADR-035-live-sensing-ui-accuracy.md docs: update ADR-035 with dark mode, render modes, pose_source fix 2026-03-02 11:08:13 -05:00
ADR-036-rvf-training-pipeline-ui.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
ADR-037-multi-person-pose-detection.md docs: ADR-037 multi-person pose detection from single ESP32 CSI stream 2026-03-02 13:49:38 -05:00
ADR-038-sublinear-goal-oriented-action-planning.md docs: ADR-038 Sublinear Goal-Oriented Action Planning (GOAP) 2026-03-02 14:39:15 -05:00
ADR-039-esp32-edge-intelligence.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
ADR-040-wasm-programmable-sensing.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
ADR-041-wasm-module-collection.md feat: expand ADR-041 WASM module catalog from 37 to 60 modules 2026-03-03 00:06:39 -05:00
ADR-042-coherent-human-channel-imaging.md feat: add ADR-042 CHCI protocol, 24 new edge modules, README restructure 2026-03-03 11:35:57 -05:00
ADR-043-sensing-server-ui-api-completion.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
ADR-044-geospatial-satellite-integration.md feat: Real-time dense point cloud from camera + WiFi CSI (#405) 2026-04-20 12:48:54 -04:00
ADR-045-amoled-display-support.md docs: update README with ADR-045–048, Observatory, adaptive classifier, AMOLED display 2026-03-05 10:20:48 -05:00
ADR-046-android-tv-box-armbian-deployment.md docs: update README with ADR-045–048, Observatory, adaptive classifier, AMOLED display 2026-03-05 10:20:48 -05:00
ADR-047-psychohistory-observatory-visualization.md docs: update README with ADR-045–048, Observatory, adaptive classifier, AMOLED display 2026-03-05 10:20:48 -05:00
ADR-048-adaptive-csi-classifier.md feat: adaptive CSI classifier with signal smoothing pipeline (ADR-048) (#144) 2026-03-05 10:15:18 -05:00
ADR-049-cross-platform-wifi-interface-detection.md chore(repo): move v1/ → archive/v1/ + add archive/README.md (#430) 2026-04-25 23:07:52 -04:00
ADR-050-provisioning-tool-enhancements.md feat: Real-time dense point cloud from camera + WiFi CSI (#405) 2026-04-20 12:48:54 -04:00
ADR-050-quality-engineering-security-hardening.md fix: security hardening — replace fake HMAC, add path traversal protection, OTA auth (ADR-050) 2026-03-06 13:11:04 -05:00
ADR-052-ddd-bounded-contexts.md feat: complete Tauri desktop frontend with all pages and enhanced design (#198) 2026-03-08 23:31:18 -04:00
ADR-052-tauri-desktop-frontend.md docs(adr): update bare wifi-densepose-rs refs to v2/ in ADR-012, ADR-052 2026-04-25 21:43:21 -04:00
ADR-053-ui-design-system.md feat: complete Tauri desktop frontend with all pages and enhanced design (#198) 2026-03-08 23:31:18 -04:00
ADR-054-desktop-full-implementation.md feat(desktop): RuView Desktop v0.4.0 - Full ADR-054 Implementation (#212) 2026-03-09 21:58:06 -04:00
ADR-055-integrated-sensing-server.md feat(desktop): v0.4.2 - Integrated sensing server with real WebSocket data 2026-03-10 00:08:31 -04:00
ADR-056-ruview-desktop-capabilities.md feat(desktop): v0.4.2 - Integrated sensing server with real WebSocket data 2026-03-10 00:08:31 -04:00
ADR-057-firmware-csi-build-guard.md fix(firmware): enable CSI in sdkconfig and add build guard (ADR-057) 2026-03-12 13:49:20 -04:00
ADR-058-ruvector-wasm-browser-pose-example.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
ADR-059-live-esp32-csi-pipeline.md feat(demo): wire all 6 RuVector WASM attention mechanisms into pose fusion 2026-03-12 20:59:57 -04:00
ADR-060-provision-channel-mac-filter.md feat(firmware): --channel and --filter-mac provisioning (ADR-060) 2026-03-13 08:27:08 -04:00
ADR-061-qemu-esp32s3-firmware-testing.md feat: QEMU ESP32-S3 testing platform + swarm configurator (ADR-061/062) (#260) 2026-03-14 13:39:51 -04:00
ADR-062-qemu-swarm-configurator.md feat: QEMU ESP32-S3 testing platform + swarm configurator (ADR-061/062) (#260) 2026-03-14 13:39:51 -04:00
ADR-063-mmwave-sensor-fusion.md feat: ADR-063/064 mmWave sensor fusion + multimodal ambient intelligence (#269) 2026-03-15 16:10:10 -04:00
ADR-064-multimodal-ambient-intelligence.md feat: ADR-063/064 mmWave sensor fusion + multimodal ambient intelligence (#269) 2026-03-15 16:10:10 -04:00
ADR-065-happiness-scoring-seed-bridge.md feat: happiness scoring pipeline + ESP32 swarm with Cognitum Seed (#285) 2026-03-20 18:46:34 -04:00
ADR-066-esp32-swarm-seed-coordinator.md feat: ADR-069 ESP32 CSI → Cognitum Seed RVF pipeline (v0.5.4-esp32) 2026-04-02 19:32:18 -04:00
ADR-067-ruvector-v2.0.5-upgrade.md docs(adr): ADR-067 RuVector v2.0.5 upgrade + new crate adoption plan 2026-03-23 21:51:43 -04:00
ADR-068-per-node-state-pipeline.md feat: ADR-069 ESP32 CSI → Cognitum Seed RVF pipeline (v0.5.4-esp32) 2026-04-02 19:32:18 -04:00
ADR-069-cognitum-seed-csi-pipeline.md feat: ADR-069 ESP32 CSI → Cognitum Seed RVF pipeline (v0.5.4-esp32) 2026-04-02 19:32:18 -04:00
ADR-070-self-supervised-pretraining.md feat: ADR-070 self-supervised pretraining from live ESP32 CSI + Seed 2026-04-02 20:42:37 -04:00
ADR-071-ruvllm-training-pipeline.md feat: camera-free 17-keypoint pose training (10 sensor signals) 2026-04-02 23:05:07 -04:00
ADR-072-wiflow-architecture.md feat: ADR-072 WiFlow SOTA architecture — TCN + axial attention + pose decoder 2026-04-02 23:40:23 -04:00
ADR-073-multifrequency-mesh-scan.md feat: ADR-074 spiking neural network for real-time CSI sensing 2026-04-03 00:34:31 -04:00
ADR-074-spiking-neural-csi-sensing.md feat: ADR-074 spiking neural network for real-time CSI sensing 2026-04-03 00:34:31 -04:00
ADR-075-mincut-person-separation.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
ADR-076-csi-spectrogram-embeddings.md feat: ADR-076 CNN spectrogram embeddings + graph transformer fusion 2026-04-03 00:36:38 -04:00
ADR-077-novel-rf-sensing-applications.md feat: ADR-077 — 6 novel RF sensing applications 2026-04-03 08:50:48 -04:00
ADR-078-multifreq-mesh-applications.md feat: ADR-078 — 5 multi-frequency mesh applications 2026-04-03 08:52:50 -04:00
ADR-079-camera-ground-truth-training.md fix: remove hardcoded Tailscale IPs and usernames from public files 2026-04-06 14:39:21 -04:00
ADR-080-qe-remediation-plan.md chore(repo): move v1/ → archive/v1/ + add archive/README.md (#430) 2026-04-25 23:07:52 -04:00
ADR-081-adaptive-csi-mesh-firmware-kernel.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
ADR-082-pose-tracker-confirmed-output-filter.md fix(tracker): exclude Lost tracks from bridge output (#420, ADR-082) (#426) 2026-04-25 20:03:03 -04:00
ADR-083-per-cluster-pi-compute-hop.md docs(adr): ADR-083 — per-cluster Pi compute hop (proposed) (#428) 2026-04-25 23:08:02 -04:00
ADR-084-rabitq-similarity-sensor.md docs(adr): ADR-084 — promote Proposed → Accepted 2026-04-26 02:22:26 -04:00
ADR-085-rabitq-pipeline-expansion.md docs(adr): ADR-085 — RaBitQ pipeline expansion (proposed) (#433) 2026-04-26 00:11:32 -04:00
ADR-086-edge-novelty-gate.md docs(adr): ADR-086 — edge novelty gate (proposed) (#434) 2026-04-26 02:21:40 -04:00
ADR-089-nvsim-nv-diamond-simulator.md feat(nvsim): full simulator stack — Rust crate, dashboard, server, App Store, Ghost Murmur [ADR-089/090/091/092/093] 2026-04-27 12:41:01 -04:00
ADR-090-nvsim-lindblad-extension.md feat(nvsim): full simulator stack — Rust crate, dashboard, server, App Store, Ghost Murmur [ADR-089/090/091/092/093] 2026-04-27 12:41:01 -04:00
ADR-091-stand-off-radar-tier-research.md feat(nvsim): full simulator stack — Rust crate, dashboard, server, App Store, Ghost Murmur [ADR-089/090/091/092/093] 2026-04-27 12:41:01 -04:00
ADR-092-nvsim-dashboard-implementation.md feat(nvsim): full simulator stack — Rust crate, dashboard, server, App Store, Ghost Murmur [ADR-089/090/091/092/093] 2026-04-27 12:41:01 -04:00
ADR-093-dashboard-gap-analysis.md feat(nvsim): full simulator stack — Rust crate, dashboard, server, App Store, Ghost Murmur [ADR-089/090/091/092/093] 2026-04-27 12:41:01 -04:00
ADR-094-pointcloud-github-pages-deployment.md feat(pointcloud): integrate ESP32 CSI as optional data stream from hosted viewer 2026-04-29 20:33:00 -04:00
ADR-095-rvcsi-edge-rf-sensing-platform.md fix(rvcsi): scale-relative baseline-drift thresholds + ESP32 end-to-end validation 2026-05-12 22:19:15 -04:00
ADR-096-rvcsi-ffi-crate-layout.md fix(rvcsi): scale-relative baseline-drift thresholds + ESP32 end-to-end validation 2026-05-12 22:19:15 -04:00
ADR-097-adopt-rvcsi-as-ruview-csi-runtime.md docs(adr): ADR-097 — adopt rvCSI as RuView's primary CSI runtime (Proposed) 2026-05-13 09:23:25 -04:00
ADR-098-evaluate-midstream-fit.md docs(adr): ADR-098 — evaluate midstream for RuView's CSI/WS/mesh pipeline (Rejected) (#553) 2026-05-17 17:49:21 -04:00
ADR-099-midstream-introspection-tap.md feat(introspection): I6 — regime-changed signal + per-frame analyze + honest ADR-099 D8 amendment 2026-05-13 23:29:37 -04:00
ADR-100-cog-packaging-specification.md docs(adr): ADR-100 + ADR-101 — record v0.0.1 shipping status (#644) 2026-05-19 17:13:31 -04:00
ADR-101-pose-estimation-cog.md docs: repoint #640 references to #645 (original deleted, replaced) (#646) 2026-05-19 17:18:05 -04:00
ADR-102-edge-module-registry.md feat(edge-registry): ADR-102 — surface Cognitum cog catalog via /api/v1/edge/registry (#648) 2026-05-19 18:08:43 -04:00
ADR-103-learned-multi-person-counter.md docs(adr): ADR-103 — learned multi-person counter (SOTA path) (#693) 2026-05-21 18:28:18 -04:00
ADR-104-ruview-mcp-cli-distribution.md feat(tools): scaffold ruview MCP server + CLI + ADR-104 (#705) 2026-05-21 23:33:18 -04:00
ADR-105-federated-csi-training.md research(R4) + adr-105: federated CSI training with MERIDIAN+Krum+mincut (#716) 2026-05-22 02:24:42 -04:00
ADR-106-dp-sgd-and-primitive-isolation.md adr-106: differential privacy + biometric primitive isolation for federation (#718) 2026-05-22 02:48:16 -04:00
ADR-107-cross-installation-federation.md adr-107: cross-installation federation with secure aggregation — privacy chain closes (#725) 2026-05-22 04:27:48 -04:00
ADR-108-kyber-post-quantum-key-exchange.md adr-108: Kyber post-quantum key exchange for cross-installation federation (#731) 2026-05-22 05:45:32 -04:00
ADR-109-dilithium-pqc-signatures.md adr-109: Dilithium PQC signatures — provenance side of post-quantum migration (#733) 2026-05-22 06:06:05 -04:00
ADR-110-esp32-c6-firmware-extension.md ADR-110: ESP32-C6 firmware extension (#764) 2026-05-23 15:34:48 -04:00
ADR-113-multistatic-placement-strategy.md adr-113: multistatic placement strategy — consolidates 9-tick R6 family into decision matrix (#734) 2026-05-22 06:17:21 -04:00
ADR-114-cog-quantum-vitals.md adr-114: cog-quantum-vitals — first quantum-augmented cog spec, recovers R13 NEGATIVE (#742) 2026-05-22 07:37:44 -04:00
ADR-115-home-assistant-integration.md ADR-115: Home Assistant + Matter integration (#778) 2026-05-23 16:13:28 -04:00
ADR-116-cog-ha-matter-seed.md cog-ha-matter (ADR-116): P4 ✅ — mDNS wired into main, broker deferred 2026-05-23 18:36:14 -04:00
ADR-117-pip-wifi-densepose-modernization.md feat(adr-117): pip wifi-densepose modernization (PIP-PHOENIX) + ruview sibling release (#786) 2026-05-24 13:00:38 -04:00
ADR-118-bfld-beamforming-feedback-layer-for-detection.md docs(adr-118): integrate Soul Signature into BFLD ADRs 118/120/121/122 2026-05-24 12:35:06 -04:00
ADR-119-bfld-frame-format-and-wire-protocol.md feat(adr-118/p1): scaffold wifi-densepose-bfld crate + frame header (3/3 tests GREEN) 2026-05-24 13:34:05 -04:00
ADR-120-bfld-privacy-class-and-hash-rotation.md docs(adr-118): integrate Soul Signature into BFLD ADRs 118/120/121/122 2026-05-24 12:35:06 -04:00
ADR-121-bfld-identity-risk-scoring.md docs(adr-118): integrate Soul Signature into BFLD ADRs 118/120/121/122 2026-05-24 12:35:06 -04:00
ADR-122-bfld-ruview-ha-matter-exposure.md docs(adr-118): integrate Soul Signature into BFLD ADRs 118/120/121/122 2026-05-24 12:35:06 -04:00
ADR-123-bfld-capture-path-nexmon-and-esp32.md docs(adr-118): BFLD — Beamforming Feedback Layer for Detection (6 ADRs + research bundle) 2026-05-24 12:20:52 -04:00
ADR-124-rvagent-mcp-ruvector-npm-integration.md docs(adr-124): RUVIEW-POLICY layer + Q4 cache resolution + multi-modal vision 2026-05-24 20:11:24 -04:00
ADR-125-ruview-apple-home-native-hap-bridge.md docs(adr-125): resolve topology + identity-risk questions per review 2026-05-25 16:02:51 -04:00
ADR-126-ruview-native-ha-port-master.md ADR-125 APPLE-FABRIC: RuView <-> Apple Home native HAP bridge (e2e on real C6) (#797) 2026-05-25 17:36:40 -04:00
ADR-127-homecore-state-machine-rust.md ADR-125 APPLE-FABRIC: RuView <-> Apple Home native HAP bridge (e2e on real C6) (#797) 2026-05-25 17:36:40 -04:00
ADR-128-homecore-integration-plugin-system.md ADR-125 APPLE-FABRIC: RuView <-> Apple Home native HAP bridge (e2e on real C6) (#797) 2026-05-25 17:36:40 -04:00
ADR-129-homecore-automation-engine.md ADR-125 APPLE-FABRIC: RuView <-> Apple Home native HAP bridge (e2e on real C6) (#797) 2026-05-25 17:36:40 -04:00
ADR-130-homecore-rest-websocket-api.md ADR-125 APPLE-FABRIC: RuView <-> Apple Home native HAP bridge (e2e on real C6) (#797) 2026-05-25 17:36:40 -04:00
ADR-133-homecore-assist-ruflo.md HOMECORE: native Rust/WASM/TS port of Home Assistant — ADRs 125-134 implementation (#800) 2026-05-25 22:47:48 -04:00
ADR-134-csi-to-cir-time-domain-multipath.md feat(signal): ADR-134 CSI→CIR via ISTA + NeumannSolver warm-start (#837) 2026-05-28 16:24:37 -04:00
ADR-135-empty-room-baseline-calibration.md feat(signal): ADR-135 — empty-room baseline calibration 2026-05-28 18:57:08 -04:00
ADR-136-ruview-streaming-engine-frame-contracts.md docs(adr): add Implementation Status & Integration to ADR-136..146 2026-05-29 08:09:23 -04:00
ADR-137-fusion-engine-quality-scoring-evidence.md docs(adr): add Implementation Status & Integration to ADR-136..146 2026-05-29 08:09:23 -04:00
ADR-138-linkgroup-array-coordinator-clock-quality.md docs(adr): add Implementation Status & Integration to ADR-136..146 2026-05-29 08:09:23 -04:00
ADR-139-worldgraph-environmental-digital-twin.md docs(adr): add Implementation Status & Integration to ADR-136..146 2026-05-29 08:09:23 -04:00
ADR-140-semantic-state-record-and-agent-bridge.md docs(adr): add Implementation Status & Integration to ADR-136..146 2026-05-29 08:09:23 -04:00
ADR-141-bfld-privacy-control-plane-modes-attestation.md docs(adr): add Implementation Status & Integration to ADR-136..146 2026-05-29 08:09:23 -04:00
ADR-142-evolution-tracker-temporal-voxel-aggregation.md docs(adr): add Implementation Status & Integration to ADR-136..146 2026-05-29 08:09:23 -04:00
ADR-143-rf-slam-reflector-discovery-anchor-learning.md docs(adr): add Implementation Status & Integration to ADR-136..146 2026-05-29 08:09:23 -04:00
ADR-144-uwb-range-constraint-fusion.md docs(adr): add Implementation Status & Integration to ADR-136..146 2026-05-29 08:09:23 -04:00
ADR-145-ablation-eval-harness-privacy-leakage.md docs(adr): add Implementation Status & Integration to ADR-136..146 2026-05-29 08:09:23 -04:00
ADR-146-rf-encoder-multitask-heads-uncertainty.md docs(adr): add Implementation Status & Integration to ADR-136..146 2026-05-29 08:09:23 -04:00
ADR-147-benchmark-proof.md docs(adr-147): add real CSI benchmark — 208ms median, 3.98GB VRAM, 72 frames/sec 2026-05-29 19:56:28 -04:00
ADR-147-nvidia-cosmos-world-foundation-model-integration.md feat(worldmodel): ADR-147 — OccWorld world model integration, wifi-densepose-worldmodel v0.3.0 (#856) 2026-05-29 16:53:51 -04:00
ADR-148-drone-swarm-control-system.md feat(swarm): add ruview-swarm crate — drone swarm control system (ADR-148) (#862) 2026-05-30 16:00:59 -04:00
README.md feat(signal): ADR-135 — empty-room baseline calibration 2026-05-28 18:57:08 -04:00

README.md

Architecture Decision Records

This folder contains 45 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
ADR-134 First-Class Channel Impulse Response (CIR) Support Proposed
ADR-135 Empty-Room Baseline Calibration (per-subcarrier Welford statistics) 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

Related

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