chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427)

The Rust port lived two directories deep (rust-port/wifi-densepose-rs/)
without any sibling under rust-port/ that warranted the extra level.
Move the whole workspace up to v2/ to match v1/ (Python) at the same
depth and shorten every cd / build command across the repo.

git mv preserves history for all tracked files. 60 files updated for
path references (CI workflows, ADRs, docs, scripts, READMEs, internal
.claude-flow state). Two manual fixes for relative-cd paths in
CLAUDE.md and ADR-043 that became wrong after the depth change
(cd ../.. → cd ..).

Validated:
- cargo check --workspace --no-default-features → clean (after target/
  nuke; the gitignored target/ was carried by the OS rename and had
  hard-coded old paths in build scripts)
- cargo test --workspace --no-default-features → 1,539 passed, 0 failed,
  8 ignored (same totals as pre-rename)
- ESP32-S3 on COM7 → still streaming live CSI (cb #40300, RSSI -64 dBm)

After-merge follow-up: contributors should `rm -rf v2/target` once and
let cargo regenerate from the new path.

.github/workflows/ci.yml

@@ -79,13 +79,13 @@ jobs:
         path: |
           ~/.cargo/registry
           ~/.cargo/git
-          rust-port/wifi-densepose-rs/target
-        key: ${{ runner.os }}-cargo-${{ hashFiles('rust-port/wifi-densepose-rs/Cargo.lock') }}
+          v2/target
+        key: ${{ runner.os }}-cargo-${{ hashFiles('v2/Cargo.lock') }}
         restore-keys: |
           ${{ runner.os }}-cargo-
 
     - name: Run Rust tests
-      working-directory: rust-port/wifi-densepose-rs
+      working-directory: v2
       run: cargo test --workspace --no-default-features
 
   # Unit and Integration Tests

.github/workflows/desktop-release.yml

@@ -40,18 +40,18 @@ jobs:
           targets: ${{ matrix.target }}
 
       - name: Install frontend dependencies
-        working-directory: rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/ui
+        working-directory: v2/crates/wifi-densepose-desktop/ui
         run: npm ci
 
       - name: Build frontend
-        working-directory: rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/ui
+        working-directory: v2/crates/wifi-densepose-desktop/ui
         run: npm run build
 
       - name: Install Tauri CLI
         run: cargo install tauri-cli --version "^2.0.0"
 
       - name: Build Tauri app
-        working-directory: rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop
+        working-directory: v2/crates/wifi-densepose-desktop
         run: cargo tauri build --target ${{ matrix.target }}
         env:
           TAURI_SIGNING_PRIVATE_KEY: ${{ secrets.TAURI_SIGNING_PRIVATE_KEY }}
@@ -68,14 +68,14 @@ jobs:
 
       - name: Package macOS app
         run: |
-          cd rust-port/wifi-densepose-rs/target/${{ matrix.target }}/release/bundle/macos
+          cd v2/target/${{ matrix.target }}/release/bundle/macos
           zip -r "RuView-Desktop-${{ github.event.inputs.version || '0.4.0' }}-macos-${{ steps.arch.outputs.arch }}.zip" "RuView Desktop.app"
 
       - name: Upload macOS artifact
         uses: actions/upload-artifact@v4
         with:
           name: ruview-macos-${{ steps.arch.outputs.arch }}
-          path: rust-port/wifi-densepose-rs/target/${{ matrix.target }}/release/bundle/macos/*.zip
+          path: v2/target/${{ matrix.target }}/release/bundle/macos/*.zip
 
   build-windows:
     name: Build Windows
@@ -93,18 +93,18 @@ jobs:
         uses: dtolnay/rust-toolchain@stable
 
       - name: Install frontend dependencies
-        working-directory: rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/ui
+        working-directory: v2/crates/wifi-densepose-desktop/ui
         run: npm ci
 
       - name: Build frontend
-        working-directory: rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/ui
+        working-directory: v2/crates/wifi-densepose-desktop/ui
         run: npm run build
 
       - name: Install Tauri CLI
         run: cargo install tauri-cli --version "^2.0.0"
 
       - name: Build Tauri app
-        working-directory: rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop
+        working-directory: v2/crates/wifi-densepose-desktop
         run: cargo tauri build
         env:
           TAURI_SIGNING_PRIVATE_KEY: ${{ secrets.TAURI_SIGNING_PRIVATE_KEY }}
@@ -114,13 +114,13 @@ jobs:
         uses: actions/upload-artifact@v4
         with:
           name: ruview-windows-msi
-          path: rust-port/wifi-densepose-rs/target/release/bundle/msi/*.msi
+          path: v2/target/release/bundle/msi/*.msi
 
       - name: Upload Windows NSIS artifact
         uses: actions/upload-artifact@v4
         with:
           name: ruview-windows-nsis
-          path: rust-port/wifi-densepose-rs/target/release/bundle/nsis/*.exe
+          path: v2/target/release/bundle/nsis/*.exe
 
   create-release:
     name: Create Release

CLAUDE.md

@@ -3,7 +3,7 @@
 ## Project: wifi-densepose
 
 WiFi-based human pose estimation using Channel State Information (CSI).
-Dual codebase: Python v1 (`v1/`) and Rust port (`rust-port/wifi-densepose-rs/`).
+Dual codebase: Python v1 (`v1/`) and Rust port (`v2/`).
 ### Key Rust Crates
 | Crate | Description |
 |-------|-------------|
@@ -84,7 +84,7 @@ All 5 ruvector crates integrated in workspace:
 ### Build & Test Commands (this repo)
 ```bash
 # Rust — full workspace tests (1,031+ tests, ~2 min)
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo test --workspace --no-default-features
 
 # Rust — single crate check (no GPU needed)
@@ -151,11 +151,11 @@ Crates must be published in dependency order:
 
 ```bash
 # 1. Rust tests — must be 1,031+ passed, 0 failed
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo test --workspace --no-default-features
 
 # 2. Python proof — must print VERDICT: PASS
-cd ../..
+cd ..
 python v1/data/proof/verify.py
 
 # 3. Generate witness bundle (includes both above + firmware hashes)
@@ -211,10 +211,10 @@ Active feature branch: `ruvsense-full-implementation` (PR #77)
 - NEVER save to root folder — use the directories below
 - `docs/adr/` — Architecture Decision Records (43 ADRs)
 - `docs/ddd/` — Domain-Driven Design models
-- `rust-port/wifi-densepose-rs/crates/` — Rust workspace crates (15 crates)
-- `rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/` — RuvSense multistatic modules (14 files)
-- `rust-port/wifi-densepose-rs/crates/wifi-densepose-ruvector/src/viewpoint/` — Cross-viewpoint fusion (5 files)
-- `rust-port/wifi-densepose-rs/crates/wifi-densepose-hardware/src/esp32/` — ESP32 TDM protocol
+- `v2/crates/` — Rust workspace crates (15 crates)
+- `v2/crates/wifi-densepose-signal/src/ruvsense/` — RuvSense multistatic modules (14 files)
+- `v2/crates/wifi-densepose-ruvector/src/viewpoint/` — Cross-viewpoint fusion (5 files)
+- `v2/crates/wifi-densepose-hardware/src/esp32/` — ESP32 TDM protocol
 - `firmware/esp32-csi-node/main/` — ESP32 C firmware (channel hopping, NVS config, TDM)
 - `v1/src/` — Python source (core, hardware, services, api)
 - `v1/data/proof/` — Deterministic CSI proof bundles

README.md

@@ -110,7 +110,7 @@ RuView now generates **real-time 3D point clouds** by fusing camera depth + WiFi
 
 **Quick start:**
 ```bash
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo build --release -p wifi-densepose-pointcloud
 ./target/release/ruview-pointcloud serve --bind 127.0.0.1:9880
 # Open http://localhost:9880 for live 3D viewer
@@ -381,7 +381,7 @@ See [ADR-069](docs/adr/ADR-069-cognitum-seed-csi-pipeline.md), [ADR-071](docs/ad
 | [Build Guide](docs/build-guide.md) | Building from source (Rust and Python) |
 | [Architecture Decisions](docs/adr/README.md) | 79 ADRs — why each technical choice was made, organized by domain (hardware, signal processing, ML, platform, infrastructure) |
 | [Domain Models](docs/ddd/README.md) | 7 DDD models (RuvSense, Signal Processing, Training Pipeline, Hardware Platform, Sensing Server, WiFi-Mat, CHCI) — bounded contexts, aggregates, domain events, and ubiquitous language |
-| [Desktop App](rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/README.md) | **WIP** — Tauri v2 desktop app for node management, OTA updates, WASM deployment, and mesh visualization |
+| [Desktop App](v2/crates/wifi-densepose-desktop/README.md) | **WIP** — Tauri v2 desktop app for node management, OTA updates, WASM deployment, and mesh visualization |
 | [Medical Examples](examples/medical/README.md) | Contactless blood pressure, heart rate, breathing rate via 60 GHz mmWave radar — $15 hardware, no wearable |
 
 ---
@@ -581,24 +581,24 @@ Small programs that run directly on the ESP32 sensor — no internet needed, no
 | ⚛️ | [**Quantum-Inspired**](docs/edge-modules/autonomous.md) | Uses quantum-inspired math to map room-wide signal coherence and search for optimal sensor configurations |
 | 🤖 | [**Autonomous & Exotic**](docs/edge-modules/autonomous.md) | Self-managing sensor mesh — auto-heals dropped nodes, plans its own actions, and explores experimental signal representations |
 
-All implemented modules are `no_std` Rust, share a [common utility library](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/vendor_common.rs), and talk to the host through a 12-function API. Full documentation: [**Edge Modules Guide**](docs/edge-modules/README.md). See the [complete implemented module list](#edge-module-list) below.
+All implemented modules are `no_std` Rust, share a [common utility library](v2/crates/wifi-densepose-wasm-edge/src/vendor_common.rs), and talk to the host through a 12-function API. Full documentation: [**Edge Modules Guide**](docs/edge-modules/README.md). See the [complete implemented module list](#edge-module-list) below.
 
 <details id="edge-module-list">
 <summary><strong>🧩 Edge Intelligence — <a href="docs/edge-modules/README.md">All 65 Modules Implemented</a></strong> (ADR-041 complete)</summary>
 
-All 60 modules are implemented, tested (609 tests passing), and ready to deploy. They compile to `wasm32-unknown-unknown`, run on ESP32-S3 via WASM3, and share a [common utility library](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/vendor_common.rs). Source: [`crates/wifi-densepose-wasm-edge/src/`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/)
+All 60 modules are implemented, tested (609 tests passing), and ready to deploy. They compile to `wasm32-unknown-unknown`, run on ESP32-S3 via WASM3, and share a [common utility library](v2/crates/wifi-densepose-wasm-edge/src/vendor_common.rs). Source: [`crates/wifi-densepose-wasm-edge/src/`](v2/crates/wifi-densepose-wasm-edge/src/)
 
 **Core modules** (ADR-040 flagship + early implementations):
 
 | Module | File | What It Does |
 |--------|------|-------------|
-| Gesture Classifier | [`gesture.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/gesture.rs) | DTW template matching for hand gestures |
-| Coherence Filter | [`coherence.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/coherence.rs) | Phase coherence gating for signal quality |
-| Adversarial Detector | [`adversarial.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/adversarial.rs) | Detects physically impossible signal patterns |
-| Intrusion Detector | [`intrusion.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/intrusion.rs) | Human vs non-human motion classification |
-| Occupancy Counter | [`occupancy.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/occupancy.rs) | Zone-level person counting |
-| Vital Trend | [`vital_trend.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/vital_trend.rs) | Long-term breathing and heart rate trending |
-| RVF Parser | [`rvf.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/rvf.rs) | RVF container format parsing |
+| Gesture Classifier | [`gesture.rs`](v2/crates/wifi-densepose-wasm-edge/src/gesture.rs) | DTW template matching for hand gestures |
+| Coherence Filter | [`coherence.rs`](v2/crates/wifi-densepose-wasm-edge/src/coherence.rs) | Phase coherence gating for signal quality |
+| Adversarial Detector | [`adversarial.rs`](v2/crates/wifi-densepose-wasm-edge/src/adversarial.rs) | Detects physically impossible signal patterns |
+| Intrusion Detector | [`intrusion.rs`](v2/crates/wifi-densepose-wasm-edge/src/intrusion.rs) | Human vs non-human motion classification |
+| Occupancy Counter | [`occupancy.rs`](v2/crates/wifi-densepose-wasm-edge/src/occupancy.rs) | Zone-level person counting |
+| Vital Trend | [`vital_trend.rs`](v2/crates/wifi-densepose-wasm-edge/src/vital_trend.rs) | Long-term breathing and heart rate trending |
+| RVF Parser | [`rvf.rs`](v2/crates/wifi-densepose-wasm-edge/src/rvf.rs) | RVF container format parsing |
 
 **Vendor-integrated modules** (24 modules, ADR-041 Category 7):
 
@@ -606,128 +606,128 @@ All 60 modules are implemented, tested (609 tests passing), and ready to deploy.
 
 | Module | File | What It Does | Budget |
 |--------|------|-------------|--------|
-| Flash Attention | [`sig_flash_attention.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/sig_flash_attention.rs) | Tiled attention over 8 subcarrier groups — finds spatial focus regions and entropy | S (<5ms) |
-| Coherence Gate | [`sig_coherence_gate.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/sig_coherence_gate.rs) | Z-score phasor gating with hysteresis: Accept / PredictOnly / Reject / Recalibrate | L (<2ms) |
-| Temporal Compress | [`sig_temporal_compress.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/sig_temporal_compress.rs) | 3-tier adaptive quantization (8-bit hot / 5-bit warm / 3-bit cold) | L (<2ms) |
-| Sparse Recovery | [`sig_sparse_recovery.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/sig_sparse_recovery.rs) | ISTA L1 reconstruction for dropped subcarriers | H (<10ms) |
-| Person Match | [`sig_mincut_person_match.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/sig_mincut_person_match.rs) | Hungarian-lite bipartite assignment for multi-person tracking | S (<5ms) |
-| Optimal Transport | [`sig_optimal_transport.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/sig_optimal_transport.rs) | Sliced Wasserstein-1 distance with 4 projections | L (<2ms) |
+| Flash Attention | [`sig_flash_attention.rs`](v2/crates/wifi-densepose-wasm-edge/src/sig_flash_attention.rs) | Tiled attention over 8 subcarrier groups — finds spatial focus regions and entropy | S (<5ms) |
+| Coherence Gate | [`sig_coherence_gate.rs`](v2/crates/wifi-densepose-wasm-edge/src/sig_coherence_gate.rs) | Z-score phasor gating with hysteresis: Accept / PredictOnly / Reject / Recalibrate | L (<2ms) |
+| Temporal Compress | [`sig_temporal_compress.rs`](v2/crates/wifi-densepose-wasm-edge/src/sig_temporal_compress.rs) | 3-tier adaptive quantization (8-bit hot / 5-bit warm / 3-bit cold) | L (<2ms) |
+| Sparse Recovery | [`sig_sparse_recovery.rs`](v2/crates/wifi-densepose-wasm-edge/src/sig_sparse_recovery.rs) | ISTA L1 reconstruction for dropped subcarriers | H (<10ms) |
+| Person Match | [`sig_mincut_person_match.rs`](v2/crates/wifi-densepose-wasm-edge/src/sig_mincut_person_match.rs) | Hungarian-lite bipartite assignment for multi-person tracking | S (<5ms) |
+| Optimal Transport | [`sig_optimal_transport.rs`](v2/crates/wifi-densepose-wasm-edge/src/sig_optimal_transport.rs) | Sliced Wasserstein-1 distance with 4 projections | L (<2ms) |
 
 **🧠 Adaptive Learning** — On-device learning without cloud connectivity
 
 | Module | File | What It Does | Budget |
 |--------|------|-------------|--------|
-| DTW Gesture Learn | [`lrn_dtw_gesture_learn.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/lrn_dtw_gesture_learn.rs) | User-teachable gesture recognition — 3-rehearsal protocol, 16 templates | S (<5ms) |
-| Anomaly Attractor | [`lrn_anomaly_attractor.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/lrn_anomaly_attractor.rs) | 4D dynamical system attractor classification with Lyapunov exponents | H (<10ms) |
-| Meta Adapt | [`lrn_meta_adapt.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/lrn_meta_adapt.rs) | Hill-climbing self-optimization with safety rollback | L (<2ms) |
-| EWC Lifelong | [`lrn_ewc_lifelong.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/lrn_ewc_lifelong.rs) | Elastic Weight Consolidation — remembers past tasks while learning new ones | S (<5ms) |
+| DTW Gesture Learn | [`lrn_dtw_gesture_learn.rs`](v2/crates/wifi-densepose-wasm-edge/src/lrn_dtw_gesture_learn.rs) | User-teachable gesture recognition — 3-rehearsal protocol, 16 templates | S (<5ms) |
+| Anomaly Attractor | [`lrn_anomaly_attractor.rs`](v2/crates/wifi-densepose-wasm-edge/src/lrn_anomaly_attractor.rs) | 4D dynamical system attractor classification with Lyapunov exponents | H (<10ms) |
+| Meta Adapt | [`lrn_meta_adapt.rs`](v2/crates/wifi-densepose-wasm-edge/src/lrn_meta_adapt.rs) | Hill-climbing self-optimization with safety rollback | L (<2ms) |
+| EWC Lifelong | [`lrn_ewc_lifelong.rs`](v2/crates/wifi-densepose-wasm-edge/src/lrn_ewc_lifelong.rs) | Elastic Weight Consolidation — remembers past tasks while learning new ones | S (<5ms) |
 
 **🗺️ Spatial Reasoning** — Location, proximity, and influence mapping
 
 | Module | File | What It Does | Budget |
 |--------|------|-------------|--------|
-| PageRank Influence | [`spt_pagerank_influence.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/spt_pagerank_influence.rs) | 4x4 cross-correlation graph with power iteration PageRank | L (<2ms) |
-| Micro HNSW | [`spt_micro_hnsw.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/spt_micro_hnsw.rs) | 64-vector navigable small-world graph for nearest-neighbor search | S (<5ms) |
-| Spiking Tracker | [`spt_spiking_tracker.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/spt_spiking_tracker.rs) | 32 LIF neurons + 4 output zone neurons with STDP learning | S (<5ms) |
+| PageRank Influence | [`spt_pagerank_influence.rs`](v2/crates/wifi-densepose-wasm-edge/src/spt_pagerank_influence.rs) | 4x4 cross-correlation graph with power iteration PageRank | L (<2ms) |
+| Micro HNSW | [`spt_micro_hnsw.rs`](v2/crates/wifi-densepose-wasm-edge/src/spt_micro_hnsw.rs) | 64-vector navigable small-world graph for nearest-neighbor search | S (<5ms) |
+| Spiking Tracker | [`spt_spiking_tracker.rs`](v2/crates/wifi-densepose-wasm-edge/src/spt_spiking_tracker.rs) | 32 LIF neurons + 4 output zone neurons with STDP learning | S (<5ms) |
 
 **⏱️ Temporal Analysis** — Activity patterns, logic verification, autonomous planning
 
 | Module | File | What It Does | Budget |
 |--------|------|-------------|--------|
-| Pattern Sequence | [`tmp_pattern_sequence.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/tmp_pattern_sequence.rs) | Activity routine detection and deviation alerts | S (<5ms) |
-| Temporal Logic Guard | [`tmp_temporal_logic_guard.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/tmp_temporal_logic_guard.rs) | LTL formula verification on CSI event streams | S (<5ms) |
-| GOAP Autonomy | [`tmp_goap_autonomy.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/tmp_goap_autonomy.rs) | Goal-Oriented Action Planning for autonomous module management | S (<5ms) |
+| Pattern Sequence | [`tmp_pattern_sequence.rs`](v2/crates/wifi-densepose-wasm-edge/src/tmp_pattern_sequence.rs) | Activity routine detection and deviation alerts | S (<5ms) |
+| Temporal Logic Guard | [`tmp_temporal_logic_guard.rs`](v2/crates/wifi-densepose-wasm-edge/src/tmp_temporal_logic_guard.rs) | LTL formula verification on CSI event streams | S (<5ms) |
+| GOAP Autonomy | [`tmp_goap_autonomy.rs`](v2/crates/wifi-densepose-wasm-edge/src/tmp_goap_autonomy.rs) | Goal-Oriented Action Planning for autonomous module management | S (<5ms) |
 
 **🛡️ AI Security** — Tamper detection and behavioral anomaly profiling
 
 | Module | File | What It Does | Budget |
 |--------|------|-------------|--------|
-| Prompt Shield | [`ais_prompt_shield.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/ais_prompt_shield.rs) | FNV-1a replay detection, injection detection (10x amplitude), jamming (SNR) | L (<2ms) |
-| Behavioral Profiler | [`ais_behavioral_profiler.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/ais_behavioral_profiler.rs) | 6D behavioral profile with Mahalanobis anomaly scoring | S (<5ms) |
+| Prompt Shield | [`ais_prompt_shield.rs`](v2/crates/wifi-densepose-wasm-edge/src/ais_prompt_shield.rs) | FNV-1a replay detection, injection detection (10x amplitude), jamming (SNR) | L (<2ms) |
+| Behavioral Profiler | [`ais_behavioral_profiler.rs`](v2/crates/wifi-densepose-wasm-edge/src/ais_behavioral_profiler.rs) | 6D behavioral profile with Mahalanobis anomaly scoring | S (<5ms) |
 
 **⚛️ Quantum-Inspired** — Quantum computing metaphors applied to CSI analysis
 
 | Module | File | What It Does | Budget |
 |--------|------|-------------|--------|
-| Quantum Coherence | [`qnt_quantum_coherence.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/qnt_quantum_coherence.rs) | Bloch sphere mapping, Von Neumann entropy, decoherence detection | S (<5ms) |
-| Interference Search | [`qnt_interference_search.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/qnt_interference_search.rs) | 16 room-state hypotheses with Grover-inspired oracle + diffusion | S (<5ms) |
+| Quantum Coherence | [`qnt_quantum_coherence.rs`](v2/crates/wifi-densepose-wasm-edge/src/qnt_quantum_coherence.rs) | Bloch sphere mapping, Von Neumann entropy, decoherence detection | S (<5ms) |
+| Interference Search | [`qnt_interference_search.rs`](v2/crates/wifi-densepose-wasm-edge/src/qnt_interference_search.rs) | 16 room-state hypotheses with Grover-inspired oracle + diffusion | S (<5ms) |
 
 **🤖 Autonomous Systems** — Self-governing and self-healing behaviors
 
 | Module | File | What It Does | Budget |
 |--------|------|-------------|--------|
-| Psycho-Symbolic | [`aut_psycho_symbolic.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/aut_psycho_symbolic.rs) | 16-rule forward-chaining knowledge base with contradiction detection | S (<5ms) |
-| Self-Healing Mesh | [`aut_self_healing_mesh.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/aut_self_healing_mesh.rs) | 8-node mesh with health tracking, degradation/recovery, coverage healing | S (<5ms) |
+| Psycho-Symbolic | [`aut_psycho_symbolic.rs`](v2/crates/wifi-densepose-wasm-edge/src/aut_psycho_symbolic.rs) | 16-rule forward-chaining knowledge base with contradiction detection | S (<5ms) |
+| Self-Healing Mesh | [`aut_self_healing_mesh.rs`](v2/crates/wifi-densepose-wasm-edge/src/aut_self_healing_mesh.rs) | 8-node mesh with health tracking, degradation/recovery, coverage healing | S (<5ms) |
 
 **🔮 Exotic (Vendor)** — Novel mathematical models for CSI interpretation
 
 | Module | File | What It Does | Budget |
 |--------|------|-------------|--------|
-| Time Crystal | [`exo_time_crystal.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/exo_time_crystal.rs) | Autocorrelation subharmonic detection in 256-frame history | S (<5ms) |
-| Hyperbolic Space | [`exo_hyperbolic_space.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/exo_hyperbolic_space.rs) | Poincare ball embedding with 32 reference locations, hyperbolic distance | S (<5ms) |
+| Time Crystal | [`exo_time_crystal.rs`](v2/crates/wifi-densepose-wasm-edge/src/exo_time_crystal.rs) | Autocorrelation subharmonic detection in 256-frame history | S (<5ms) |
+| Hyperbolic Space | [`exo_hyperbolic_space.rs`](v2/crates/wifi-densepose-wasm-edge/src/exo_hyperbolic_space.rs) | Poincare ball embedding with 32 reference locations, hyperbolic distance | S (<5ms) |
 
 **🏥 Medical & Health** (Category 1) — Contactless health monitoring
 
 | Module | File | What It Does | Budget |
 |--------|------|-------------|--------|
-| Sleep Apnea | [`med_sleep_apnea.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/med_sleep_apnea.rs) | Detects breathing pauses during sleep | S (<5ms) |
-| Cardiac Arrhythmia | [`med_cardiac_arrhythmia.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/med_cardiac_arrhythmia.rs) | Monitors heart rate for irregular rhythms | S (<5ms) |
-| Respiratory Distress | [`med_respiratory_distress.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/med_respiratory_distress.rs) | Alerts on abnormal breathing patterns | S (<5ms) |
-| Gait Analysis | [`med_gait_analysis.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/med_gait_analysis.rs) | Tracks walking patterns and detects changes | S (<5ms) |
-| Seizure Detection | [`med_seizure_detect.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/med_seizure_detect.rs) | 6-state machine for tonic-clonic seizure recognition | S (<5ms) |
+| Sleep Apnea | [`med_sleep_apnea.rs`](v2/crates/wifi-densepose-wasm-edge/src/med_sleep_apnea.rs) | Detects breathing pauses during sleep | S (<5ms) |
+| Cardiac Arrhythmia | [`med_cardiac_arrhythmia.rs`](v2/crates/wifi-densepose-wasm-edge/src/med_cardiac_arrhythmia.rs) | Monitors heart rate for irregular rhythms | S (<5ms) |
+| Respiratory Distress | [`med_respiratory_distress.rs`](v2/crates/wifi-densepose-wasm-edge/src/med_respiratory_distress.rs) | Alerts on abnormal breathing patterns | S (<5ms) |
+| Gait Analysis | [`med_gait_analysis.rs`](v2/crates/wifi-densepose-wasm-edge/src/med_gait_analysis.rs) | Tracks walking patterns and detects changes | S (<5ms) |
+| Seizure Detection | [`med_seizure_detect.rs`](v2/crates/wifi-densepose-wasm-edge/src/med_seizure_detect.rs) | 6-state machine for tonic-clonic seizure recognition | S (<5ms) |
 
 **🔐 Security & Safety** (Category 2) — Perimeter and threat detection
 
 | Module | File | What It Does | Budget |
 |--------|------|-------------|--------|
-| Perimeter Breach | [`sec_perimeter_breach.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/sec_perimeter_breach.rs) | Detects boundary crossings with approach/departure | S (<5ms) |
-| Weapon Detection | [`sec_weapon_detect.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/sec_weapon_detect.rs) | Metal anomaly detection via CSI amplitude shifts | S (<5ms) |
-| Tailgating | [`sec_tailgating.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/sec_tailgating.rs) | Detects unauthorized follow-through at access points | S (<5ms) |
-| Loitering | [`sec_loitering.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/sec_loitering.rs) | Alerts when someone lingers too long in a zone | S (<5ms) |
-| Panic Motion | [`sec_panic_motion.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/sec_panic_motion.rs) | Detects fleeing, struggling, or panic movement | S (<5ms) |
+| Perimeter Breach | [`sec_perimeter_breach.rs`](v2/crates/wifi-densepose-wasm-edge/src/sec_perimeter_breach.rs) | Detects boundary crossings with approach/departure | S (<5ms) |
+| Weapon Detection | [`sec_weapon_detect.rs`](v2/crates/wifi-densepose-wasm-edge/src/sec_weapon_detect.rs) | Metal anomaly detection via CSI amplitude shifts | S (<5ms) |
+| Tailgating | [`sec_tailgating.rs`](v2/crates/wifi-densepose-wasm-edge/src/sec_tailgating.rs) | Detects unauthorized follow-through at access points | S (<5ms) |
+| Loitering | [`sec_loitering.rs`](v2/crates/wifi-densepose-wasm-edge/src/sec_loitering.rs) | Alerts when someone lingers too long in a zone | S (<5ms) |
+| Panic Motion | [`sec_panic_motion.rs`](v2/crates/wifi-densepose-wasm-edge/src/sec_panic_motion.rs) | Detects fleeing, struggling, or panic movement | S (<5ms) |
 
 **🏢 Smart Building** (Category 3) — Automation and energy efficiency
 
 | Module | File | What It Does | Budget |
 |--------|------|-------------|--------|
-| HVAC Presence | [`bld_hvac_presence.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/bld_hvac_presence.rs) | Occupancy-driven HVAC control with departure countdown | S (<5ms) |
-| Lighting Zones | [`bld_lighting_zones.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/bld_lighting_zones.rs) | Auto-dim/off lighting based on zone activity | S (<5ms) |
-| Elevator Count | [`bld_elevator_count.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/bld_elevator_count.rs) | Counts people entering/leaving with overload warning | S (<5ms) |
-| Meeting Room | [`bld_meeting_room.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/bld_meeting_room.rs) | Tracks meeting lifecycle: start, headcount, end, availability | S (<5ms) |
-| Energy Audit | [`bld_energy_audit.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/bld_energy_audit.rs) | Tracks after-hours usage and room utilization rates | S (<5ms) |
+| HVAC Presence | [`bld_hvac_presence.rs`](v2/crates/wifi-densepose-wasm-edge/src/bld_hvac_presence.rs) | Occupancy-driven HVAC control with departure countdown | S (<5ms) |
+| Lighting Zones | [`bld_lighting_zones.rs`](v2/crates/wifi-densepose-wasm-edge/src/bld_lighting_zones.rs) | Auto-dim/off lighting based on zone activity | S (<5ms) |
+| Elevator Count | [`bld_elevator_count.rs`](v2/crates/wifi-densepose-wasm-edge/src/bld_elevator_count.rs) | Counts people entering/leaving with overload warning | S (<5ms) |
+| Meeting Room | [`bld_meeting_room.rs`](v2/crates/wifi-densepose-wasm-edge/src/bld_meeting_room.rs) | Tracks meeting lifecycle: start, headcount, end, availability | S (<5ms) |
+| Energy Audit | [`bld_energy_audit.rs`](v2/crates/wifi-densepose-wasm-edge/src/bld_energy_audit.rs) | Tracks after-hours usage and room utilization rates | S (<5ms) |
 
 **🛒 Retail & Hospitality** (Category 4) — Customer insights without cameras
 
 | Module | File | What It Does | Budget |
 |--------|------|-------------|--------|
-| Queue Length | [`ret_queue_length.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/ret_queue_length.rs) | Estimates queue size and wait times | S (<5ms) |
-| Dwell Heatmap | [`ret_dwell_heatmap.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/ret_dwell_heatmap.rs) | Shows where people spend time (hot/cold zones) | S (<5ms) |
-| Customer Flow | [`ret_customer_flow.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/ret_customer_flow.rs) | Counts ins/outs and tracks net occupancy | S (<5ms) |
-| Table Turnover | [`ret_table_turnover.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/ret_table_turnover.rs) | Restaurant table lifecycle: seated, dining, vacated | S (<5ms) |
-| Shelf Engagement | [`ret_shelf_engagement.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/ret_shelf_engagement.rs) | Detects browsing, considering, and reaching for products | S (<5ms) |
+| Queue Length | [`ret_queue_length.rs`](v2/crates/wifi-densepose-wasm-edge/src/ret_queue_length.rs) | Estimates queue size and wait times | S (<5ms) |
+| Dwell Heatmap | [`ret_dwell_heatmap.rs`](v2/crates/wifi-densepose-wasm-edge/src/ret_dwell_heatmap.rs) | Shows where people spend time (hot/cold zones) | S (<5ms) |
+| Customer Flow | [`ret_customer_flow.rs`](v2/crates/wifi-densepose-wasm-edge/src/ret_customer_flow.rs) | Counts ins/outs and tracks net occupancy | S (<5ms) |
+| Table Turnover | [`ret_table_turnover.rs`](v2/crates/wifi-densepose-wasm-edge/src/ret_table_turnover.rs) | Restaurant table lifecycle: seated, dining, vacated | S (<5ms) |
+| Shelf Engagement | [`ret_shelf_engagement.rs`](v2/crates/wifi-densepose-wasm-edge/src/ret_shelf_engagement.rs) | Detects browsing, considering, and reaching for products | S (<5ms) |
 
 **🏭 Industrial & Specialized** (Category 5) — Safety and compliance
 
 | Module | File | What It Does | Budget |
 |--------|------|-------------|--------|
-| Forklift Proximity | [`ind_forklift_proximity.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/ind_forklift_proximity.rs) | Warns when people get too close to vehicles | S (<5ms) |
-| Confined Space | [`ind_confined_space.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/ind_confined_space.rs) | OSHA-compliant worker monitoring with extraction alerts | S (<5ms) |
-| Clean Room | [`ind_clean_room.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/ind_clean_room.rs) | Occupancy limits and turbulent motion detection | S (<5ms) |
-| Livestock Monitor | [`ind_livestock_monitor.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/ind_livestock_monitor.rs) | Animal presence, stillness, and escape alerts | S (<5ms) |
-| Structural Vibration | [`ind_structural_vibration.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/ind_structural_vibration.rs) | Seismic events, mechanical resonance, structural drift | S (<5ms) |
+| Forklift Proximity | [`ind_forklift_proximity.rs`](v2/crates/wifi-densepose-wasm-edge/src/ind_forklift_proximity.rs) | Warns when people get too close to vehicles | S (<5ms) |
+| Confined Space | [`ind_confined_space.rs`](v2/crates/wifi-densepose-wasm-edge/src/ind_confined_space.rs) | OSHA-compliant worker monitoring with extraction alerts | S (<5ms) |
+| Clean Room | [`ind_clean_room.rs`](v2/crates/wifi-densepose-wasm-edge/src/ind_clean_room.rs) | Occupancy limits and turbulent motion detection | S (<5ms) |
+| Livestock Monitor | [`ind_livestock_monitor.rs`](v2/crates/wifi-densepose-wasm-edge/src/ind_livestock_monitor.rs) | Animal presence, stillness, and escape alerts | S (<5ms) |
+| Structural Vibration | [`ind_structural_vibration.rs`](v2/crates/wifi-densepose-wasm-edge/src/ind_structural_vibration.rs) | Seismic events, mechanical resonance, structural drift | S (<5ms) |
 
 **🔮 Exotic & Research** (Category 6) — Experimental sensing applications
 
 | Module | File | What It Does | Budget |
 |--------|------|-------------|--------|
-| Dream Stage | [`exo_dream_stage.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/exo_dream_stage.rs) | Contactless sleep stage classification (wake/light/deep/REM) | S (<5ms) |
-| Emotion Detection | [`exo_emotion_detect.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/exo_emotion_detect.rs) | Arousal, stress, and calm detection from micro-movements | S (<5ms) |
-| Gesture Language | [`exo_gesture_language.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/exo_gesture_language.rs) | Sign language letter recognition via WiFi | S (<5ms) |
-| Music Conductor | [`exo_music_conductor.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/exo_music_conductor.rs) | Tempo and dynamic tracking from conducting gestures | S (<5ms) |
-| Plant Growth | [`exo_plant_growth.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/exo_plant_growth.rs) | Monitors plant growth, circadian rhythms, wilt detection | S (<5ms) |
-| Ghost Hunter | [`exo_ghost_hunter.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/exo_ghost_hunter.rs) | Environmental anomaly classification (draft/insect/wind/unknown) | S (<5ms) |
-| Rain Detection | [`exo_rain_detect.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/exo_rain_detect.rs) | Detects rain onset, intensity, and cessation via signal scatter | S (<5ms) |
-| Breathing Sync | [`exo_breathing_sync.rs`](rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/exo_breathing_sync.rs) | Detects synchronized breathing between multiple people | S (<5ms) |
+| Dream Stage | [`exo_dream_stage.rs`](v2/crates/wifi-densepose-wasm-edge/src/exo_dream_stage.rs) | Contactless sleep stage classification (wake/light/deep/REM) | S (<5ms) |
+| Emotion Detection | [`exo_emotion_detect.rs`](v2/crates/wifi-densepose-wasm-edge/src/exo_emotion_detect.rs) | Arousal, stress, and calm detection from micro-movements | S (<5ms) |
+| Gesture Language | [`exo_gesture_language.rs`](v2/crates/wifi-densepose-wasm-edge/src/exo_gesture_language.rs) | Sign language letter recognition via WiFi | S (<5ms) |
+| Music Conductor | [`exo_music_conductor.rs`](v2/crates/wifi-densepose-wasm-edge/src/exo_music_conductor.rs) | Tempo and dynamic tracking from conducting gestures | S (<5ms) |
+| Plant Growth | [`exo_plant_growth.rs`](v2/crates/wifi-densepose-wasm-edge/src/exo_plant_growth.rs) | Monitors plant growth, circadian rhythms, wilt detection | S (<5ms) |
+| Ghost Hunter | [`exo_ghost_hunter.rs`](v2/crates/wifi-densepose-wasm-edge/src/exo_ghost_hunter.rs) | Environmental anomaly classification (draft/insect/wind/unknown) | S (<5ms) |
+| Rain Detection | [`exo_rain_detect.rs`](v2/crates/wifi-densepose-wasm-edge/src/exo_rain_detect.rs) | Detects rain onset, intensity, and cessation via signal scatter | S (<5ms) |
+| Breathing Sync | [`exo_breathing_sync.rs`](v2/crates/wifi-densepose-wasm-edge/src/exo_breathing_sync.rs) | Detects synchronized breathing between multiple people | S (<5ms) |
 
 </details>
 
@@ -855,7 +855,7 @@ git clone https://github.com/ruvnet/RuView.git
 cd RuView
 
 # Rust (primary — 810x faster)
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo build --release
 cargo test --workspace
 
@@ -950,7 +950,7 @@ cargo add wifi-densepose-ruvector   # RuVector v2.0.4 integration layer (ADR-017
 
 All crates integrate with [RuVector v2.0.4](https://github.com/ruvnet/ruvector) — see [AI Backbone](#ai-backbone-ruvector) below.
 
-**[rUv Neural](rust-port/wifi-densepose-rs/crates/ruv-neural/)** — A separate 12-crate workspace for brain network topology analysis, neural decoding, and medical sensing. See [rUv Neural](#ruv-neural) in Models & Training.
+**[rUv Neural](v2/crates/ruv-neural/)** — A separate 12-crate workspace for brain network topology analysis, neural decoding, and medical sensing. See [rUv Neural](#ruv-neural) in Models & Training.
 
 </details>
 
@@ -1050,7 +1050,7 @@ The neural pipeline uses a graph transformer with cross-attention to map CSI fea
 | [RVF Model Container](#rvf-model-container) | Binary packaging with Ed25519 signing, progressive 3-layer loading, SIMD quantization | [ADR-023](docs/adr/ADR-023-trained-densepose-model-ruvector-pipeline.md) |
 | [Training & Fine-Tuning](#training--fine-tuning) | 8-phase pure Rust pipeline (7,832 lines), MM-Fi/Wi-Pose pre-training, 6-term composite loss, SONA LoRA | [ADR-023](docs/adr/ADR-023-trained-densepose-model-ruvector-pipeline.md) |
 | [RuVector Crates](#ruvector-crates) | 11 vendored Rust crates from [ruvector](https://github.com/ruvnet/ruvector): attention, min-cut, solver, GNN, HNSW, temporal compression, sparse inference | [GitHub](https://github.com/ruvnet/ruvector) · [Source](vendor/ruvector/) |
-| [rUv Neural](#ruv-neural) | 12-crate brain topology analysis ecosystem: neural decoding, quantum sensor integration, cognitive state classification, BCI output | [README](rust-port/wifi-densepose-rs/crates/ruv-neural/README.md) |
+| [rUv Neural](#ruv-neural) | 12-crate brain topology analysis ecosystem: neural decoding, quantum sensor integration, cognitive state classification, BCI output | [README](v2/crates/ruv-neural/README.md) |
 | [AI Backbone (RuVector)](#ai-backbone-ruvector) | 5 AI capabilities replacing hand-tuned thresholds: attention, graph min-cut, sparse solvers, tiered compression | [crates.io](https://crates.io/crates/wifi-densepose-ruvector) |
 | [Self-Learning WiFi AI (ADR-024)](#self-learning-wifi-ai-adr-024) | Contrastive self-supervised learning, room fingerprinting, anomaly detection, 55 KB model | [ADR-024](docs/adr/ADR-024-contrastive-csi-embedding-model.md) |
 | [Cross-Environment Generalization (ADR-027)](docs/adr/ADR-027-cross-environment-domain-generalization.md) | Domain-adversarial training, geometry-conditioned inference, hardware normalization, zero-shot deployment | [ADR-027](docs/adr/ADR-027-cross-environment-domain-generalization.md) |
@@ -1168,7 +1168,7 @@ Bundle verify:  7/7 checks PASS
 **Verify it yourself** (no hardware needed):
 ```bash
 # Run all tests
-cd rust-port/wifi-densepose-rs && cargo test --workspace --no-default-features
+cd v2 && cargo test --workspace --no-default-features
 
 # Run the deterministic proof
 python v1/data/proof/verify.py
@@ -1484,7 +1484,7 @@ See [firmware/esp32-csi-node/README.md](firmware/esp32-csi-node/README.md), [ADR
 | WASM Support | No | Yes |
 
 ```bash
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo build --release
 cargo test --workspace
 cargo bench --package wifi-densepose-signal
@@ -1781,7 +1781,7 @@ The full RuVector ecosystem includes 90+ crates. See [github.com/ruvnet/ruvector
 <details>
 <summary><a id="ruv-neural"></a><strong>🧠 rUv Neural</strong> — Brain topology analysis ecosystem for neural decoding and medical sensing</summary>
 
-[**rUv Neural**](rust-port/wifi-densepose-rs/crates/ruv-neural/README.md) is a 12-crate Rust ecosystem that extends RuView's signal processing into brain network topology analysis. It transforms neural magnetic field measurements from quantum sensors (NV diamond magnetometers, optically pumped magnetometers) into dynamic connectivity graphs, using minimum cut algorithms to detect cognitive state transitions in real time. The ecosystem includes crates for signal processing (`ruv-neural-signal`), graph construction (`ruv-neural-graph`), HNSW-indexed pattern memory (`ruv-neural-memory`), graph embeddings (`ruv-neural-embed`), cognitive state decoding (`ruv-neural-decoder`), and ESP32/WASM edge targets. Medical and research applications include early neurological disease detection via topology signatures, brain-computer interfaces, clinical neurofeedback, and non-invasive biomedical sensing -- bridging RuView's RF sensing architecture with the emerging field of quantum biomedical diagnostics.
+[**rUv Neural**](v2/crates/ruv-neural/README.md) is a 12-crate Rust ecosystem that extends RuView's signal processing into brain network topology analysis. It transforms neural magnetic field measurements from quantum sensors (NV diamond magnetometers, optically pumped magnetometers) into dynamic connectivity graphs, using minimum cut algorithms to detect cognitive state transitions in real time. The ecosystem includes crates for signal processing (`ruv-neural-signal`), graph construction (`ruv-neural-graph`), HNSW-indexed pattern memory (`ruv-neural-memory`), graph embeddings (`ruv-neural-embed`), cognitive state decoding (`ruv-neural-decoder`), and ESP32/WASM edge targets. Medical and research applications include early neurological disease detection via topology signatures, brain-computer interfaces, clinical neurofeedback, and non-invasive biomedical sensing -- bridging RuView's RF sensing architecture with the emerging field of quantum biomedical diagnostics.
 
 </details>
 
@@ -2154,7 +2154,7 @@ wifi-densepose tasks list               # List background tasks
 
 ```bash
 # Rust tests (primary — 542+ tests)
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo test --workspace
 
 # Sensing server tests (229 tests)
@@ -2258,7 +2258,7 @@ git clone https://github.com/ruvnet/RuView.git
 cd RuView
 
 # Rust development
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo build --release
 cargo test --workspace
 

docker/Dockerfile.rust

@@ -8,8 +8,8 @@ FROM rust:1.85-bookworm AS builder
 WORKDIR /build
 
 # Copy workspace files
-COPY rust-port/wifi-densepose-rs/Cargo.toml rust-port/wifi-densepose-rs/Cargo.lock ./
-COPY rust-port/wifi-densepose-rs/crates/ ./crates/
+COPY v2/Cargo.toml v2/Cargo.lock ./
+COPY v2/crates/ ./crates/
 
 # Copy vendored RuVector crates
 COPY vendor/ruvector/ /build/vendor/ruvector/

docs/WITNESS-LOG-028.md

@@ -35,7 +35,7 @@ git checkout 96b01008
 ### Step 2: Rust Workspace — Full Test Suite
 
 ```bash
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo test --workspace --no-default-features
 ```
 
@@ -89,7 +89,7 @@ ls firmware/esp32-csi-node/build/*.bin 2>/dev/null || echo "App binary in build/
 ### Step 6: Verify ADR-018 Binary Frame Parser
 
 ```bash
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo test -p wifi-densepose-hardware --no-default-features
 ```
 

docs/adr/ADR-002-ruvector-rvf-integration-strategy.md

@@ -216,4 +216,4 @@ full = ["mincut-matching", "attn-mincut", "temporal-compress", "solver-interpola
 - [Elastic Weight Consolidation](https://arxiv.org/abs/1612.00796)
 - [Raft Consensus](https://raft.github.io/raft.pdf)
 - [ML-DSA (FIPS 204)](https://csrc.nist.gov/pubs/fips/204/final)
-- [WiFi-DensePose Rust ADR-001: Workspace Structure](../rust-port/wifi-densepose-rs/docs/adr/ADR-001-workspace-structure.md)
+- [WiFi-DensePose Rust ADR-001: Workspace Structure](../v2/docs/adr/ADR-001-workspace-structure.md)

docs/adr/ADR-017-ruvector-signal-mat-integration.md

@@ -510,7 +510,7 @@ impl CompressedHeartbeatSpectrogram {
 
 ## Dependency Changes Required
 
-Add to `rust-port/wifi-densepose-rs/Cargo.toml` workspace (already present from ADR-016):
+Add to `v2/Cargo.toml` workspace (already present from ADR-016):
 ```toml
 ruvector-mincut = "2.0.4"          # already present
 ruvector-attn-mincut = "2.0.4"    # already present

docs/adr/ADR-019-sensing-only-ui-mode.md

@@ -11,7 +11,7 @@
 
 The WiFi-DensePose UI was originally built to require the full FastAPI DensePose backend (`localhost:8000`) for all functionality. This backend depends on heavy Python packages (PyTorch ~2GB, torchvision, OpenCV, SQLAlchemy, Redis) making it impractical for lightweight sensing-only deployments where the user simply wants to visualize live WiFi signal data from ESP32 CSI or Windows RSSI collectors.
 
-A Rust port exists (`rust-port/wifi-densepose-rs`) using Axum with lighter runtime footprint (~10MB binary, ~5MB RAM), but it still requires libtorch C++ bindings and OpenBLAS for compilation—a non-trivial build.
+A Rust port exists (`v2`) using Axum with lighter runtime footprint (~10MB binary, ~5MB RAM), but it still requires libtorch C++ bindings and OpenBLAS for compilation—a non-trivial build.
 
 Users need a way to run the UI with **only the sensing pipeline** active, without installing the full DensePose backend stack.
 

docs/adr/ADR-020-rust-ruvector-ai-model-migration.md

@@ -22,7 +22,7 @@ The current Python DensePose backend requires ~2GB+ of dependencies:
 
 This makes the DensePose backend impractical for edge deployments, CI pipelines, and developer laptops where users only need WiFi sensing + pose estimation.
 
-Meanwhile, the Rust port at `rust-port/wifi-densepose-rs/` already has:
+Meanwhile, the Rust port at `v2/` already has:
 
 - **12 workspace crates** covering core, signal, nn, api, db, config, hardware, wasm, cli, mat, train
 - **5 RuVector crates** (v2.0.4, published on crates.io) integrated into signal, mat, and train crates
@@ -143,7 +143,7 @@ The `wifi-densepose-nn::onnx` module loads `.onnx` files directly.
 
 ```bash
 # Build the Rust workspace (ONNX-only, no libtorch)
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo check --workspace 2>&1
 
 # Build release binary

docs/adr/ADR-021-vital-sign-detection-rvdna-pipeline.md

@@ -34,7 +34,7 @@ The `vendor/ruvector` codebase provides a rich set of signal processing primitiv
 
 ### Current Project State
 
-The Rust port (`rust-port/wifi-densepose-rs/`) already contains:
+The Rust port (`v2/`) already contains:
 
 - **`wifi-densepose-signal`**: CSI processing, BVP extraction, phase sanitization, Hampel filter, spectrogram generation, Fresnel geometry, motion detection, subcarrier selection
 - **`wifi-densepose-sensing-server`**: Axum server receiving ESP32 CSI frames (UDP 5005), WebSocket broadcasting sensing updates, signal field generation, with three data source modes:
@@ -108,7 +108,7 @@ ESP32 CSI (UDP:5005) ──▶│  ┌──────────────
 ### Module Structure
 
 ```
-rust-port/wifi-densepose-rs/crates/wifi-densepose-vitals/
+v2/crates/wifi-densepose-vitals/
 ├── Cargo.toml
 └── src/
     ├── lib.rs                 # Public API and re-exports

docs/adr/ADR-022-windows-wifi-enhanced-fidelity-ruvector.md

@@ -592,7 +592,7 @@ impl FrameBuilder {
 ### 3.3 Module Structure
 
 ```
-rust-port/wifi-densepose-rs/crates/wifi-densepose-wifiscan/
+v2/crates/wifi-densepose-wifiscan/
 ├── Cargo.toml
 └── src/
     ├── lib.rs                    # Public API, re-exports

docs/adr/ADR-023-trained-densepose-model-ruvector-pipeline.md

@@ -699,28 +699,28 @@ let dashboard = container.load_dashboard()?;
 
 | File | Purpose |
 |------|---------|
-| `rust-port/.../wifi-densepose-train/src/dataset_mmfi.rs` | MM-Fi dataset loader with subcarrier resampling |
-| `rust-port/.../wifi-densepose-train/src/dataset_wipose.rs` | Wi-Pose dataset loader |
-| `rust-port/.../wifi-densepose-train/src/graph_transformer.rs` | Graph transformer integration |
-| `rust-port/.../wifi-densepose-train/src/body_gnn.rs` | GNN body graph reasoning |
-| `rust-port/.../wifi-densepose-train/src/adaptation.rs` | SONA LoRA + EWC++ adaptation |
-| `rust-port/.../wifi-densepose-train/src/trainer.rs` | Training loop with multi-term loss |
+| `v2/.../wifi-densepose-train/src/dataset_mmfi.rs` | MM-Fi dataset loader with subcarrier resampling |
+| `v2/.../wifi-densepose-train/src/dataset_wipose.rs` | Wi-Pose dataset loader |
+| `v2/.../wifi-densepose-train/src/graph_transformer.rs` | Graph transformer integration |
+| `v2/.../wifi-densepose-train/src/body_gnn.rs` | GNN body graph reasoning |
+| `v2/.../wifi-densepose-train/src/adaptation.rs` | SONA LoRA + EWC++ adaptation |
+| `v2/.../wifi-densepose-train/src/trainer.rs` | Training loop with multi-term loss |
 | `scripts/generate_densepose_labels.py` | Teacher-student UV label generation |
 | `scripts/benchmark_inference.py` | Inference latency benchmarking |
-| `rust-port/.../wifi-densepose-train/src/rvf_builder.rs` | RVF container build pipeline |
-| `rust-port/.../wifi-densepose-train/src/bin/build_rvf.rs` | CLI binary for building `.rvf` containers |
-| `rust-port/.../wifi-densepose-train/src/bin/verify_rvf.rs` | CLI binary for verifying `.rvf` containers |
+| `v2/.../wifi-densepose-train/src/rvf_builder.rs` | RVF container build pipeline |
+| `v2/.../wifi-densepose-train/src/bin/build_rvf.rs` | CLI binary for building `.rvf` containers |
+| `v2/.../wifi-densepose-train/src/bin/verify_rvf.rs` | CLI binary for verifying `.rvf` containers |
 
 ### Modified Files
 
 | File | Change |
 |------|--------|
-| `rust-port/.../wifi-densepose-train/Cargo.toml` | Add ruvector-gnn, graph-transformer, sona, sparse-inference, math, rvf-types, rvf-wire, rvf-manifest, rvf-index, rvf-quant, rvf-crypto, rvf-runtime deps |
-| `rust-port/.../wifi-densepose-train/src/model.rs` | Integrate graph transformer + GNN layers |
-| `rust-port/.../wifi-densepose-train/src/losses.rs` | Add optimal transport + GNN edge consistency loss terms |
-| `rust-port/.../wifi-densepose-train/src/config.rs` | Add training hyperparameters for new components |
-| `rust-port/.../sensing-server/Cargo.toml` | Add rvf-runtime, rvf-types, rvf-index, rvf-quant deps |
-| `rust-port/.../sensing-server/src/main.rs` | Add `--model` flag, load `.rvf` container, progressive startup, serve embedded dashboard |
+| `v2/.../wifi-densepose-train/Cargo.toml` | Add ruvector-gnn, graph-transformer, sona, sparse-inference, math, rvf-types, rvf-wire, rvf-manifest, rvf-index, rvf-quant, rvf-crypto, rvf-runtime deps |
+| `v2/.../wifi-densepose-train/src/model.rs` | Integrate graph transformer + GNN layers |
+| `v2/.../wifi-densepose-train/src/losses.rs` | Add optimal transport + GNN edge consistency loss terms |
+| `v2/.../wifi-densepose-train/src/config.rs` | Add training hyperparameters for new components |
+| `v2/.../sensing-server/Cargo.toml` | Add rvf-runtime, rvf-types, rvf-index, rvf-quant deps |
+| `v2/.../sensing-server/src/main.rs` | Add `--model` flag, load `.rvf` container, progressive startup, serve embedded dashboard |
 
 ## Consequences
 

docs/adr/ADR-024-contrastive-csi-embedding-model.md

@@ -371,7 +371,7 @@ ESP32 SRAM budget: 520 KB. Model at INT8: 53-60 KB = 10-12% of SRAM. Ample margi
 
 ### 2.6 Concrete Module Additions
 
-All new/modified files in `rust-port/wifi-densepose-rs/crates/wifi-densepose-sensing-server/src/`:
+All new/modified files in `v2/crates/wifi-densepose-sensing-server/src/`:
 
 #### 2.6.1 `embedding.rs` (NEW, ~450 lines)
 

docs/adr/ADR-025-macos-corewlan-wifi-sensing.md

@@ -107,7 +107,7 @@ Implement a **macOS CoreWLAN sensing adapter** as a Swift helper binary + Rust a
 
 ### 3.2 Swift Helper Binary
 
-**File:** `rust-port/wifi-densepose-rs/tools/macos-wifi-scan/main.swift`
+**File:** `v2/tools/macos-wifi-scan/main.swift`
 
 ```swift
 // Modes:

docs/adr/ADR-036-rvf-training-pipeline-ui.md

@@ -198,16 +198,16 @@ When a `.rvf` model is loaded:
 ### New Files
 - `ui/components/ModelPanel.js` — Model library, inspector, load/unload controls
 - `ui/components/TrainingPanel.js` — Recording controls, training progress, metric charts
-- `rust-port/.../sensing-server/src/recording.rs` — CSI recording API handlers
-- `rust-port/.../sensing-server/src/training_api.rs` — Training API handlers + WS progress stream
-- `rust-port/.../sensing-server/src/model_manager.rs` — Model loading, hot-swap, 32LoRA activation
+- `v2/.../sensing-server/src/recording.rs` — CSI recording API handlers
+- `v2/.../sensing-server/src/training_api.rs` — Training API handlers + WS progress stream
+- `v2/.../sensing-server/src/model_manager.rs` — Model loading, hot-swap, 32LoRA activation
 - `data/models/` — Default model storage directory
 
 ### Modified Files
-- `rust-port/.../sensing-server/src/main.rs` — Wire recording, training, and model APIs
-- `rust-port/.../train/src/trainer.rs` — Add WebSocket progress callback, LoRA training mode
-- `rust-port/.../train/src/dataset.rs` — MM-Fi and Wi-Pose dataset loaders
-- `rust-port/.../nn/src/onnx.rs` — LoRA weight injection, INT8 quantization support
+- `v2/.../sensing-server/src/main.rs` — Wire recording, training, and model APIs
+- `v2/.../train/src/trainer.rs` — Add WebSocket progress callback, LoRA training mode
+- `v2/.../train/src/dataset.rs` — MM-Fi and Wi-Pose dataset loaders
+- `v2/.../nn/src/onnx.rs` — LoRA weight injection, INT8 quantization support
 - `ui/components/LiveDemoTab.js` — Model selector, LoRA dropdown, A/B spsplit view
 - `ui/components/SettingsPanel.js` — Model and training configuration sections
 - `ui/components/PoseDetectionCanvas.js` — Pose trail rendering, confidence heatmap overlay

docs/adr/ADR-039-esp32-edge-intelligence.md

@@ -128,7 +128,7 @@ All configurable via `provision.py --edge-tier 2 --pres-thresh 0.05 ...`
 - `firmware/esp32-csi-node/main/edge_processing.h` — Types and API
 - `firmware/esp32-csi-node/main/ota_update.c/h` — HTTP OTA endpoint
 - `firmware/esp32-csi-node/main/power_mgmt.c/h` — Power management
-- `rust-port/.../wifi-densepose-sensing-server/src/main.rs` — Vitals parser + REST endpoint
+- `v2/.../wifi-densepose-sensing-server/src/main.rs` — Vitals parser + REST endpoint
 - `scripts/provision.py` — Edge config CLI arguments
 - `.github/workflows/firmware-ci.yml` — CI build + size gate (updated to 950 KB for Tier 3)
 

docs/adr/ADR-040-wasm-programmable-sensing.md

@@ -164,8 +164,8 @@ Core 1 (DSP Task)
 - `firmware/esp32-csi-node/main/wasm_runtime.c/h` — Runtime host with 12 API bindings + manifest
 - `firmware/esp32-csi-node/main/wasm_upload.c/h` — HTTP REST endpoints (RVF-aware)
 - `firmware/esp32-csi-node/main/rvf_parser.c/h` — RVF container parser and verifier
-- `rust-port/.../wifi-densepose-wasm-edge/` — Rust WASM crate (gesture, coherence, adversarial, rvf, occupancy, vital_trend, intrusion)
-- `rust-port/.../wifi-densepose-sensing-server/src/main.rs` — `0xC5110004` parser
+- `v2/.../wifi-densepose-wasm-edge/` — Rust WASM crate (gesture, coherence, adversarial, rvf, occupancy, vital_trend, intrusion)
+- `v2/.../wifi-densepose-sensing-server/src/main.rs` — `0xC5110004` parser
 - `docs/adr/ADR-039-esp32-edge-intelligence.md` — Updated with Tier 3 reference
 
 ---

docs/adr/ADR-043-sensing-server-ui-api-completion.md

@@ -289,7 +289,7 @@ Startup creates `data/models/` and `data/recordings/` directories and populates
 
 ```bash
 # 1. Start sensing server with auto source (simulated fallback)
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo run -p wifi-densepose-sensing-server -- --http-port 3000 --source auto
 
 # 2. Verify model endpoints return 200
@@ -312,11 +312,11 @@ curl -s http://localhost:3000/api/v1/models/lora/profiles | jq '.'
 # Navigate to http://localhost:3000/ui/
 
 # 7. Run mobile tests
-cd ../../ui/mobile
+cd ../ui/mobile
 npx jest --no-coverage
 
 # 8. Run Rust workspace tests (must pass, 1031+ tests)
-cd ../../rust-port/wifi-densepose-rs
+cd ../../v2
 cargo test --workspace --no-default-features
 ```
 

docs/adr/ADR-052-tauri-desktop-frontend.md

@@ -52,7 +52,7 @@ Build a Tauri v2 desktop application as a new crate in the Rust workspace. The f
 Add a new crate to the workspace:
 
 ```
-rust-port/wifi-densepose-rs/
+v2/
   Cargo.toml                          # Add "crates/wifi-densepose-desktop" to members
   crates/
     wifi-densepose-desktop/           # NEW — Tauri app crate
@@ -621,11 +621,11 @@ chrono = { version = "0.4", features = ["serde"] }
 ```bash
 # Prerequisites
 cargo install tauri-cli@^2
-cd rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/frontend
+cd v2/crates/wifi-densepose-desktop/frontend
 npm install
 
 # Development (hot-reload frontend + Rust rebuild)
-cd rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop
+cd v2/crates/wifi-densepose-desktop
 cargo tauri dev
 
 # Production build
@@ -805,6 +805,6 @@ Total estimated effort: ~11 weeks for a single developer.
 - ADR-051: Sensing Server Decomposition
 - `firmware/esp32-csi-node/` — ESP32 firmware source
 - `firmware/esp32-csi-node/provision.py` — Current provisioning script
-- `rust-port/wifi-densepose-rs/crates/wifi-densepose-sensing-server/` — Sensing server
-- `rust-port/wifi-densepose-rs/crates/wifi-densepose-hardware/` — Hardware crate
+- `v2/crates/wifi-densepose-sensing-server/` — Sensing server
+- `v2/crates/wifi-densepose-hardware/` — Hardware crate
 - `ui/` — Existing web UI

docs/adr/ADR-058-ruvector-wasm-browser-pose-example.md

@@ -214,7 +214,7 @@ examples/wasm-browser-pose/
 set -e
 
 # Build wifi-densepose-wasm (CSI processing)
-wasm-pack build ../../rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm \
+wasm-pack build ../../v2/crates/wifi-densepose-wasm \
   --target web --out-dir "$(pwd)/pkg/wifi_densepose_wasm" --no-typescript
 
 # Build ruvector-cnn-wasm (CNN inference for both video and CSI)

docs/adr/ADR-075-mincut-person-separation.md

@@ -191,5 +191,5 @@ Also does not give per-person subcarrier assignments.
 
 - Stoer, M. & Wagner, F. (1997). "A Simple Min-Cut Algorithm." JACM 44(4).
 - `vendor/ruvector/crates/ruvector-mincut/src/algorithm/mod.rs` — DynamicMinCut API
-- `rust-port/.../sig_mincut_person_match.rs` — current (broken) WASM edge matcher
+- `v2/.../sig_mincut_person_match.rs` — current (broken) WASM edge matcher
 - `scripts/rf-scan.js` — CSI packet parsing and subcarrier classification

docs/adr/ADR-081-adaptive-csi-mesh-firmware-kernel.md

@@ -481,7 +481,7 @@ make check
 # → test_rv_mesh:             27/27 pass, HEALTH roundtrip = 1.0 µs
 
 # Rust-side radio_ops trait + mesh decoder tests
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo test -p wifi-densepose-hardware --no-default-features --lib radio_ops
 # → 8 passed; verifies MockRadio, CRC32 parity with firmware vectors,
 #   HEALTH encode/decode roundtrip, bad-magic/short/CRC rejection,

docs/build-guide.md

@@ -191,7 +191,7 @@ A high-performance Rust port with ~810x speedup over the Python pipeline for the
 ### Build
 
 ```bash
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo build --release
 ```
 
@@ -200,7 +200,7 @@ Release profile is configured with LTO, single codegen unit, and `-O3` for maxim
 ### Test
 
 ```bash
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo test --workspace
 ```
 
@@ -209,7 +209,7 @@ Runs 107 tests across all workspace crates.
 ### Benchmark
 
 ```bash
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo bench --package wifi-densepose-signal
 ```
 
@@ -468,7 +468,7 @@ The aggregator collects UDP streams from all ESP32 nodes, performs feature-level
 docker compose -f docker-compose.esp32.yml up
 
 # Or run the Rust aggregator directly
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo run --release --package wifi-densepose-hardware -- --mode esp32-aggregator --port 5000
 ```
 
@@ -516,7 +516,7 @@ rustup target add wasm32-unknown-unknown
 Build:
 
 ```bash
-cd rust-port/wifi-densepose-rs
+cd v2
 
 # Build WASM package (outputs to pkg/)
 wasm-pack build crates/wifi-densepose-wasm --target web --release
@@ -601,7 +601,7 @@ uvicorn v1.src.api.main:app \
   --workers 4
 
 # Or run the Rust API server
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo run --release --package wifi-densepose-api
 ```
 
@@ -631,7 +631,7 @@ pytest --cov=wifi_densepose --cov-report=html
 Rust:
 
 ```bash
-cd rust-port/wifi-densepose-rs
+cd v2
 
 # Build in debug mode (faster compilation)
 cargo build
@@ -674,7 +674,7 @@ python3 -m http.server 3000 --directory ui
 | `v1/data/proof/expected_features.sha256` | Published expected hash |
 | `v1/src/api/main.py` | FastAPI application entry point |
 | `v1/src/sensing/` | Commodity WiFi sensing module (RSSI) |
-| `rust-port/wifi-densepose-rs/Cargo.toml` | Rust workspace root |
+| `v2/Cargo.toml` | Rust workspace root |
 | `ui/viz.html` | Three.js 3D visualization |
 | `Dockerfile` | Multi-stage Docker build (dev/prod/test/security) |
 | `docker-compose.yml` | Development stack (Postgres, Redis, Prometheus, Grafana) |

docs/ddd/hardware-platform-domain-model.md

@@ -14,7 +14,7 @@ This document defines the system using [Domain-Driven Design](https://martinfowl
 | 4 | [Aggregation](#4-aggregation-context) | Server-side CSI frame reception, timestamp alignment, multi-node feature fusion | [ADR-012](../adr/ADR-012-esp32-csi-sensor-mesh.md) | `crates/wifi-densepose-hardware/src/esp32/` |
 | 5 | [Provisioning](#5-provisioning-context) | NVS configuration, firmware lifecycle, fleet management, deployment presets | [ADR-044](../adr/ADR-044-provisioning-tool-enhancements.md) | `firmware/esp32-csi-node/provision.py` |
 
-All firmware paths are relative to the repository root. Rust crate paths are relative to `rust-port/wifi-densepose-rs/`.
+All firmware paths are relative to the repository root. Rust crate paths are relative to `v2/`.
 
 ---
 

docs/ddd/ruvsense-domain-model.md

@@ -16,7 +16,7 @@ This document defines the system using [Domain-Driven Design](https://martinfowl
 | 6 | [Spatial Identity](#6-spatial-identity-context) | Cross-room tracking via environment fingerprints | [ADR-030](../adr/ADR-030-ruvsense-persistent-field-model.md) | `signal/src/ruvsense/cross_room.rs` |
 | 7 | [Edge Intelligence](#7-edge-intelligence-context) | On-device sensing (no server needed) | [ADR-039](../adr/ADR-039-esp32-edge-intelligence.md), [ADR-040](../adr/ADR-040-wasm-programmable-sensing.md) | `firmware/esp32-csi-node/main/edge_processing.c` |
 
-All code paths shown are relative to `rust-port/wifi-densepose-rs/crates/wifi-densepose-` unless otherwise noted.
+All code paths shown are relative to `v2/crates/wifi-densepose-` unless otherwise noted.
 
 ---
 

docs/ddd/sensing-server-domain-model.md

@@ -14,7 +14,7 @@ This document defines the system using [Domain-Driven Design](https://martinfowl
 | 4 | [Training Pipeline](#4-training-pipeline-context) | Background training runs, progress streaming, contrastive pretraining | [ADR-043](../adr/ADR-043-sensing-server-ui-api-completion.md) | `sensing-server/src/training_api.rs` |
 | 5 | [Visualization](#5-visualization-context) | WebSocket streaming to web UI, Gaussian splat rendering, data transparency | [ADR-019](../adr/ADR-019-sensing-only-ui-mode.md), [ADR-035](../adr/ADR-035-live-sensing-ui-accuracy.md) | `ui/` |
 
-All code paths shown are relative to `rust-port/wifi-densepose-rs/crates/wifi-densepose-` unless otherwise noted.
+All code paths shown are relative to `v2/crates/wifi-densepose-` unless otherwise noted.
 
 ---
 

docs/ddd/training-pipeline-domain-model.md

@@ -13,7 +13,7 @@ This document defines the system using [Domain-Driven Design](https://martinfowl
 | 3 | [Training Orchestration](#3-training-orchestration-context) | Run the training loop, compute composite loss, checkpoint, and verify deterministic proofs | [ADR-015](../adr/ADR-015-public-dataset-training-strategy.md), [ADR-016](../adr/ADR-016-ruvector-integration.md) | `train/src/trainer.rs`, `train/src/losses.rs`, `train/src/metrics.rs`, `train/src/proof.rs` |
 | 4 | [Embedding & Transfer](#4-embedding--transfer-context) | Produce AETHER contrastive embeddings, MERIDIAN domain-generalized features, and LoRA adapters | [ADR-024](../adr/ADR-024-contrastive-csi-embedding-model.md), [ADR-027](../adr/ADR-027-cross-environment-domain-generalization.md) | `train/src/embedding.rs`, `train/src/domain.rs`, `train/src/sona.rs` |
 
-All code paths shown are relative to `rust-port/wifi-densepose-rs/crates/wifi-densepose-` unless otherwise noted.
+All code paths shown are relative to `v2/crates/wifi-densepose-` unless otherwise noted.
 
 ---
 

docs/edge-modules/README.md

@@ -6,7 +6,7 @@
 
 ```bash
 # Build all modules for ESP32
-cd rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge
+cd v2/crates/wifi-densepose-wasm-edge
 cargo build --target wasm32-unknown-unknown --release
 
 # Run all 632 tests
@@ -144,4 +144,4 @@ Every module talks to the ESP32 through 12 functions:
 - [ADR-039](../adr/ADR-039-esp32-edge-intelligence.md) — Edge processing tiers
 - [ADR-040](../adr/ADR-040-wasm-programmable-sensing.md) — WASM runtime design
 - [ADR-041](../adr/ADR-041-wasm-module-collection.md) — Full module specification
-- [Source code](../../rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/)
+- [Source code](../../v2/crates/wifi-densepose-wasm-edge/src/)

docs/edge-modules/core.md

@@ -481,7 +481,7 @@ std::fs::write("my-gesture-v2.rvf", &rvf_mut)?;
 From the crate directory:
 
 ```bash
-cd rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge
+cd v2/crates/wifi-densepose-wasm-edge
 cargo test --features std -- gesture coherence adversarial intrusion occupancy vital_trend rvf
 ```
 

docs/edge-modules/medical.md

@@ -618,7 +618,7 @@ for _ in 0..100 {
 All medical modules include comprehensive unit tests covering initialization, normal operation, clinical scenario detection, edge cases, and cooldown behavior.
 
 ```bash
-cd rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge
+cd v2/crates/wifi-densepose-wasm-edge
 cargo test --features std -- med_
 ```
 

docs/edge-modules/security.md

@@ -556,7 +556,7 @@ for &(event_id, value) in events {
 
 ```bash
 # Run all security module tests (requires std feature)
-cd rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge
+cd v2/crates/wifi-densepose-wasm-edge
 cargo test --features std -- sec_ intrusion
 ```
 

docs/qe-reports/02-security-review.md

@@ -413,9 +413,9 @@ The `create_user()` method accepts any password without minimum length, complexi
 ### INFORMATIONAL-001: Rust API, DB, and Config Crates Are Stubs
 
 **Files:**
-- `rust-port/wifi-densepose-rs/crates/wifi-densepose-api/src/lib.rs` -- `//! WiFi-DensePose REST API (stub)`
-- `rust-port/wifi-densepose-rs/crates/wifi-densepose-db/src/lib.rs` -- `//! WiFi-DensePose database layer (stub)`
-- `rust-port/wifi-densepose-rs/crates/wifi-densepose-config/src/lib.rs` -- `//! WiFi-DensePose configuration (stub)`
+- `v2/crates/wifi-densepose-api/src/lib.rs` -- `//! WiFi-DensePose REST API (stub)`
+- `v2/crates/wifi-densepose-db/src/lib.rs` -- `//! WiFi-DensePose database layer (stub)`
+- `v2/crates/wifi-densepose-config/src/lib.rs` -- `//! WiFi-DensePose configuration (stub)`
 
 **Description:**
 The Rust API, database, and configuration crates contain only single-line stub comments. No security review of Rust API endpoints, database queries, or configuration handling was possible because no implementation exists. The `wifi-densepose-sensing-server` crate contains the actual Rust server implementation.
@@ -426,7 +426,7 @@ The Rust API, database, and configuration crates contain only single-line stub c
 
 ### INFORMATIONAL-002: Rust `unsafe` Blocks in WASM Edge Crate
 
-**Files:** `rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/*.rs` (multiple files)
+**Files:** `v2/crates/wifi-densepose-wasm-edge/src/*.rs` (multiple files)
 
 **Description:**
 The `wifi-densepose-wasm-edge` crate contains approximately 40 `unsafe` blocks, primarily for:
@@ -518,7 +518,7 @@ The following areas demonstrate security-conscious design:
 - `v1/src/tasks/backup.py` (partial) -- Subprocess command construction
 - `v1/test_auth_rate_limit.py` (partial) -- Test credentials review
 
-### Rust (rust-port/wifi-densepose-rs/)
+### Rust (v2/)
 - `crates/wifi-densepose-api/src/lib.rs` (1 line -- stub)
 - `crates/wifi-densepose-db/src/lib.rs` (1 line -- stub)
 - `crates/wifi-densepose-config/src/lib.rs` (1 line -- stub)

docs/qe-reports/03-performance-analysis.md

@@ -40,7 +40,7 @@ The WiFi-DensePose codebase is a real-time sensing system targeting 20 Hz output
 
 ### FINDING PERF-R01: Tomography Weight Matrix -- O(L * nx * ny * nz) per Link [CRITICAL]
 
-**File**: `rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/tomography.rs`  
+**File**: `v2/crates/wifi-densepose-signal/src/ruvsense/tomography.rs`  
 **Lines**: 345-383 (`compute_link_weights`)
 
 The `compute_link_weights` function iterates over every voxel in the grid for every link to compute Fresnel-zone intersection weights:
@@ -76,7 +76,7 @@ for iz in 0..config.nz {
 
 ### FINDING PERF-R02: Multistatic Fusion -- sin()/cos() per Subcarrier per Node [HIGH]
 
-**File**: `rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/multistatic.rs`  
+**File**: `v2/crates/wifi-densepose-signal/src/ruvsense/multistatic.rs`  
 **Lines**: 287-298 (`attention_weighted_fusion`)
 
 ```rust
@@ -105,7 +105,7 @@ for (n, (&amp, &ph)) in amplitudes.iter().zip(phases.iter()).enumerate() {
 
 ### FINDING PERF-R03: Pose Tracker find_track -- Linear Search [MEDIUM]
 
-**File**: `rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/pose_tracker.rs`  
+**File**: `v2/crates/wifi-densepose-signal/src/ruvsense/pose_tracker.rs`  
 **Lines**: 546-553
 
 ```rust
@@ -124,7 +124,7 @@ pub fn find_track(&self, id: TrackId) -> Option<&PoseTrack> {
 
 ### FINDING PERF-R04: Multistatic FusedSensingFrame -- Deep Clone of node_frames [HIGH]
 
-**File**: `rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/multistatic.rs`  
+**File**: `v2/crates/wifi-densepose-signal/src/ruvsense/multistatic.rs`  
 **Line**: 222
 
 ```rust
@@ -150,7 +150,7 @@ Ok(FusedSensingFrame {
 
 ### FINDING PERF-R05: Coherence Score -- Efficient but exp() in Hot Loop [LOW]
 
-**File**: `rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/coherence.rs`  
+**File**: `v2/crates/wifi-densepose-signal/src/ruvsense/coherence.rs`  
 **Lines**: 224-252 (`coherence_score`)
 
 ```rust
@@ -174,7 +174,7 @@ for i in 0..n {
 
 ### FINDING PERF-R06: Gesture DTW -- O(N * M) per Template [MEDIUM]
 
-**File**: `rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/gesture.rs`  
+**File**: `v2/crates/wifi-densepose-signal/src/ruvsense/gesture.rs`  
 **Lines**: 288-328 (`dtw_distance`)
 
 The DTW implementation uses the Sakoe-Chiba band constraint (good), but allocates two full Vec<f64> per call:
@@ -199,7 +199,7 @@ With T templates and band_width=5, complexity is O(T * N * band_width * feature_
 
 ### FINDING PERF-R07: Field Model Covariance -- O(S^2) Memory [MEDIUM]
 
-**File**: `rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/field_model.rs`  
+**File**: `v2/crates/wifi-densepose-signal/src/ruvsense/field_model.rs`  
 **Line**: 330 (`covariance_sum: Option<Array2<f64>>`)
 
 The full covariance matrix for SVD is S x S where S = number of subcarriers. With S=56, this is 56 * 56 * 8 = 25 KB -- reasonable. But the diagonal_fallback (lines 338-383) creates unnecessary intermediate allocations.
@@ -212,7 +212,7 @@ The full covariance matrix for SVD is S x S where S = number of subcarriers. Wit
 
 ### FINDING PERF-R08: Multiband Duplicate Frequency Check -- O(N^2) [LOW]
 
-**File**: `rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/multiband.rs`  
+**File**: `v2/crates/wifi-densepose-signal/src/ruvsense/multiband.rs`  
 **Lines**: 126-135
 
 ```rust
@@ -235,7 +235,7 @@ for i in 0..self.frequencies.len() {
 
 ### FINDING PERF-R09: Adversarial Detector -- Potential O(L^2) Consistency Check [MEDIUM]
 
-**File**: `rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/adversarial.rs`  
+**File**: `v2/crates/wifi-densepose-signal/src/ruvsense/adversarial.rs`  
 **Lines**: 147+
 
 The multi-link consistency check compares energy ratios across all links. With L=12 links, the pairwise comparison (if implemented) would be O(L^2) = 144. Combined with the four independent checks (consistency, field model, temporal, energy), this runs on every frame.
@@ -259,7 +259,7 @@ The multi-link consistency check compares energy ratios across all links. With L
 
 ### FINDING PERF-NN01: Serial Batch Inference [CRITICAL]
 
-**File**: `rust-port/wifi-densepose-rs/crates/wifi-densepose-nn/src/inference.rs`  
+**File**: `v2/crates/wifi-densepose-nn/src/inference.rs`  
 **Lines**: 334-336
 
 ```rust
@@ -283,7 +283,7 @@ pub fn infer_batch(&self, inputs: &[Tensor]) -> NnResult<Vec<Tensor>> {
 
 ### FINDING PERF-NN02: Async Stats Update Spawns Tokio Task per Inference [HIGH]
 
-**File**: `rust-port/wifi-densepose-rs/crates/wifi-densepose-nn/src/inference.rs`  
+**File**: `v2/crates/wifi-densepose-nn/src/inference.rs`  
 **Lines**: 311-315
 
 ```rust
@@ -307,7 +307,7 @@ tokio::spawn(async move {
 
 ### FINDING PERF-NN03: Tensor Clone in run_single [MEDIUM]
 
-**File**: `rust-port/wifi-densepose-rs/crates/wifi-densepose-nn/src/inference.rs`  
+**File**: `v2/crates/wifi-densepose-nn/src/inference.rs`  
 **Lines**: 122
 
 ```rust
@@ -326,7 +326,7 @@ fn run_single(&self, input: &Tensor) -> NnResult<Tensor> {
 
 ### FINDING PERF-NN04: WiFiDensePosePipeline -- Two Sequential Inferences [MEDIUM]
 
-**File**: `rust-port/wifi-densepose-rs/crates/wifi-densepose-nn/src/inference.rs`  
+**File**: `v2/crates/wifi-densepose-nn/src/inference.rs`  
 **Lines**: 389-413
 
 ```rust
@@ -634,7 +634,7 @@ uint32_t next = (s_ring.head + 1) & (EDGE_RING_SLOTS - 1);
 
 ### FINDING PERF-XC01: Missing Parallelism in Multistatic Pipeline [HIGH]
 
-**File**: `rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/mod.rs`  
+**File**: `v2/crates/wifi-densepose-signal/src/ruvsense/mod.rs`  
 **Lines**: 183-232
 
 The `RuvSensePipeline` orchestrator processes stages sequentially. The multiband fusion and phase alignment stages for each node are independent and could run in parallel using Rayon:
@@ -756,26 +756,26 @@ The following patterns were checked and found to be well-implemented:
 ## Appendix A: File Paths Analyzed
 
 ### Rust Signal Processing
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/mod.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/tomography.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/multistatic.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/pose_tracker.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/field_model.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/gesture.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/coherence.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/coherence_gate.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/multiband.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/phase_align.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/adversarial.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/intention.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/longitudinal.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/cross_room.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/temporal_gesture.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/attractor_drift.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/mod.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/tomography.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/multistatic.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/pose_tracker.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/field_model.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/gesture.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/coherence.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/coherence_gate.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/multiband.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/phase_align.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/adversarial.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/intention.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/longitudinal.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/cross_room.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/temporal_gesture.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-signal/src/ruvsense/attractor_drift.rs`
 
 ### Rust Neural Network
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-nn/src/inference.rs`
-- `/workspaces/ruview/rust-port/wifi-densepose-rs/crates/wifi-densepose-nn/src/tensor.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-nn/src/inference.rs`
+- `/workspaces/ruview/v2/crates/wifi-densepose-nn/src/tensor.rs`
 
 ### Python Pipeline
 - `/workspaces/ruview/v1/src/core/csi_processor.py`

docs/qe-reports/04-test-analysis.md

@@ -3,7 +3,7 @@
 **Project:** wifi-densepose (ruview)
 **Date:** 2026-04-05
 **Analyst:** QE Test Architect (V3)
-**Scope:** All test suites across Python (v1), Rust (rust-port), and Mobile (ui/mobile)
+**Scope:** All test suites across Python (v1), Rust (v2), and Mobile (ui/mobile)
 
 ---
 
@@ -470,8 +470,8 @@ This is the best-tested service in the mobile suite.
 |------|---------------|
 | `v1/tests/unit/test_sensing.py` | 45 tests with mathematical rigor, known-signal validation, domain-specific edge cases, cross-receiver agreement, band isolation. No mocks for core logic. |
 | `v1/tests/unit/test_esp32_binary_parser.py` | Real UDP socket testing, struct-level binary validation, ADR-018 compliance. Tests actual I/Q to amplitude/phase math. |
-| `rust-port/.../tests/validation_test.rs` | Physics-based validation (Doppler, phase unwrapping, spectral analysis). Tests prove algorithm correctness, not just non-failure. |
-| `rust-port/.../tests/test_losses.rs` | Deterministic data, feature-gated, tests mathematical properties (zero loss for identical inputs, non-zero for mismatched). |
+| `v2/.../tests/validation_test.rs` | Physics-based validation (Doppler, phase unwrapping, spectral analysis). Tests prove algorithm correctness, not just non-failure. |
+| `v2/.../tests/test_losses.rs` | Deterministic data, feature-gated, tests mathematical properties (zero loss for identical inputs, non-zero for mismatched). |
 | `ui/mobile/.../utils/ringBuffer.test.ts` | Comprehensive boundary testing (NaN, Infinity, 0, negative, overflow). Tests copy semantics. |
 
 ### 5.2 Worst Test Files (Needs Improvement)

docs/research/rf-topological-sensing/10-system-architecture-prototype.md

@@ -337,7 +337,7 @@ Usage in rf_topology:
 ### 3.1 Module Location
 
 ```
-rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/
+v2/crates/wifi-densepose-signal/src/ruvsense/
   rf_topology.rs          <-- New module (primary)
   rf_topology/
     graph.rs              <-- RfGraph aggregate root
@@ -351,7 +351,7 @@ rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/
 Alternatively, rf_topology could be a standalone crate:
 
 ```
-rust-port/wifi-densepose-rs/crates/wifi-densepose-topology/
+v2/crates/wifi-densepose-topology/
   src/
     lib.rs
     graph.rs

docs/security-audit-wasm-edge-vendor.md

@@ -2,7 +2,7 @@
 
 **Date**: 2026-03-03
 **Auditor**: Security Auditor Agent (Claude Opus 4.6)
-**Scope**: All 29 `.rs` files in `rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/`
+**Scope**: All 29 `.rs` files in `v2/crates/wifi-densepose-wasm-edge/src/`
 **Crate version**: 0.3.0
 **Target**: `wasm32-unknown-unknown` (ESP32-S3 WASM3 interpreter)
 

docs/tutorials/cognitum-seed-pretraining.md

@@ -909,7 +909,7 @@ For users with the Rust toolchain, the `wifi-densepose-train` crate
 provides the full training pipeline with RuVector integration:
 
 ```bash
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo run -p wifi-densepose-train -- \
   --data pretrain-vectors.rvf \
   --epochs 50 \

docs/user-guide.md

@@ -119,7 +119,7 @@ This prepares the native GTK/WebKit dependencies used by the desktop/Tauri crate
 
 ```bash
 git clone https://github.com/ruvnet/RuView.git
-cd RuView/rust-port/wifi-densepose-rs
+cd RuView/v2
 
 # Build
 cargo build --release
@@ -558,7 +558,7 @@ RuView can generate real-time 3D point clouds by fusing camera depth estimation
 
 ```bash
 # Build the pointcloud binary
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo build --release -p wifi-densepose-pointcloud
 
 # Start the server (auto-detects camera + CSI). Loopback-only by default.

docs/wifi-mat-user-guide.md

@@ -92,7 +92,7 @@ sudo apt-get install -y build-essential pkg-config libssl-dev
 ```bash
 # Clone the repository
 git clone https://github.com/ruvnet/wifi-densepose.git
-cd wifi-densepose/rust-port/wifi-densepose-rs
+cd wifi-densepose/v2
 
 # Build the wifi-mat crate
 cargo build --release --package wifi-densepose-mat

examples/happiness-vector/README.md

@@ -159,7 +159,7 @@ The happiness scoring algorithm also exists as a WASM module for on-device execu
 
 ```bash
 # Build the happiness scorer WASM
-cd rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge
+cd v2/crates/wifi-densepose-wasm-edge
 cargo build --bin ghost_hunter --target wasm32-unknown-unknown --release --no-default-features
 
 # Output: target/wasm32-unknown-unknown/release/ghost_hunter.wasm (5.7 KB)
@@ -201,6 +201,6 @@ This system is designed to be privacy-preserving by construction:
 
 - [ADR-065](../../docs/adr/ADR-065-happiness-scoring-seed-bridge.md) — Happiness scoring pipeline architecture
 - [ADR-066](../../docs/adr/ADR-066-esp32-swarm-seed-coordinator.md) — ESP32 swarm with Seed coordinator
-- [exo_happiness_score.rs](../../rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm-edge/src/exo_happiness_score.rs) — WASM edge module (Rust)
+- [exo_happiness_score.rs](../../v2/crates/wifi-densepose-wasm-edge/src/exo_happiness_score.rs) — WASM edge module (Rust)
 - [swarm_bridge.c](../../firmware/esp32-csi-node/main/swarm_bridge.c) — ESP32 firmware swarm bridge
 - [ruview_live.py](../ruview_live.py) — RuView Live dashboard with `--mode happiness`

install.sh

@@ -25,7 +25,7 @@
 set -euo pipefail
 
 SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-RUST_DIR="${SCRIPT_DIR}/rust-port/wifi-densepose-rs"
+RUST_DIR="${SCRIPT_DIR}/v2"
 
 # ─── Colors ───────────────────────────────────────────────────────────
 if [ -t 1 ]; then
@@ -955,7 +955,7 @@ post_install() {
             ;;
         rust)
             echo "    # Run benchmarks:"
-            echo "    cd rust-port/wifi-densepose-rs"
+            echo "    cd v2"
             echo "    cargo bench --package wifi-densepose-signal"
             echo ""
             echo "    # Start Rust API server:"
@@ -963,7 +963,7 @@ post_install() {
             ;;
         browser)
             echo "    # WASM package is at:"
-            echo "    # rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm/pkg/"
+            echo "    # v2/crates/wifi-densepose-wasm/pkg/"
             echo ""
             echo "    # Open the 3D visualization:"
             echo "    python3 -m http.server 3000 --directory ui"
@@ -999,17 +999,17 @@ post_install() {
             echo "    # WiFi-Mat disaster response module built."
             echo ""
             echo "    # Run WiFi-Mat tests:"
-            echo "    cd rust-port/wifi-densepose-rs"
+            echo "    cd v2"
             echo "    cargo test --package wifi-densepose-mat"
             echo ""
             echo "    # Field deployment WASM package at:"
-            echo "    # rust-port/wifi-densepose-rs/crates/wifi-densepose-wasm/pkg/"
+            echo "    # v2/crates/wifi-densepose-wasm/pkg/"
             ;;
         full)
             echo "    # Verification:  ./verify"
             echo "    # Python API:    uvicorn v1.src.api.main:app --host 0.0.0.0 --port 8000"
-            echo "    # Rust API:      cd rust-port/wifi-densepose-rs && cargo run --release --package wifi-densepose-api"
-            echo "    # Benchmarks:    cd rust-port/wifi-densepose-rs && cargo bench"
+            echo "    # Rust API:      cd v2 && cargo run --release --package wifi-densepose-api"
+            echo "    # Benchmarks:    cd v2 && cargo bench"
             echo "    # Visualization: python3 -m http.server 3000 --directory ui"
             echo "    # Docker:        docker compose up"
             ;;

rust-port/wifi-densepose-rs/.claude-flow/daemon.pid

@@ -1 +0,0 @@
-26601

rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/.claude-flow/data/pending-insights.jsonl

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rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/.claude-flow/sessions/current.json

@@ -1,12 +0,0 @@
-{
-  "id": "session-1773150558480",
-  "startedAt": "2026-03-10T13:49:18.480Z",
-  "cwd": "/Users/cohen/GitHub/ruvnet/RuView/rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop",
-  "context": {},
-  "metrics": {
-    "edits": 9,
-    "commands": 0,
-    "tasks": 0,
-    "errors": 0
-  }
-}

rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/.claude-flow/sessions/session-1773100562538.json

@@ -1,14 +0,0 @@
-{
-  "id": "session-1773100562538",
-  "startedAt": "2026-03-09T23:56:02.538Z",
-  "cwd": "/Users/cohen/GitHub/ruvnet/RuView/rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop",
-  "context": {},
-  "metrics": {
-    "edits": 13,
-    "commands": 0,
-    "tasks": 0,
-    "errors": 0
-  },
-  "endedAt": "2026-03-10T00:07:15.557Z",
-  "duration": 673020
-}

rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/.claude-flow/sessions/session-1773101285009.json

@@ -1,14 +0,0 @@
-{
-  "id": "session-1773101285009",
-  "startedAt": "2026-03-10T00:08:05.009Z",
-  "cwd": "/Users/cohen/GitHub/ruvnet/RuView/rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop",
-  "context": {},
-  "metrics": {
-    "edits": 19,
-    "commands": 0,
-    "tasks": 0,
-    "errors": 0
-  },
-  "endedAt": "2026-03-10T13:48:30.150Z",
-  "duration": 49225141
-}

rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/ui/.claude-flow/data/pending-insights.jsonl

@@ -1,28 +0,0 @@
-{"type":"edit","file":"unknown","timestamp":1772835768740,"sessionId":null}
-{"type":"edit","file":"unknown","timestamp":1772835786050,"sessionId":null}
-{"type":"edit","file":"unknown","timestamp":1772835802335,"sessionId":null}
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-{"type":"edit","file":"unknown","timestamp":1772835952451,"sessionId":null}
-{"type":"edit","file":"unknown","timestamp":1773070971487,"sessionId":null}
-{"type":"edit","file":"unknown","timestamp":1773070977376,"sessionId":null}
-{"type":"edit","file":"unknown","timestamp":1773101503481,"sessionId":null}
-{"type":"edit","file":"unknown","timestamp":1773107530083,"sessionId":null}
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-{"type":"edit","file":"unknown","timestamp":1773114830434,"sessionId":null}
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-{"type":"edit","file":"unknown","timestamp":1773150683839,"sessionId":null}
-{"type":"edit","file":"unknown","timestamp":1773150688912,"sessionId":null}

rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/ui/.claude-flow/sessions/current.json

@@ -1,12 +0,0 @@
-{
-  "id": "session-1773103750755",
-  "startedAt": "2026-03-10T00:49:10.755Z",
-  "cwd": "/Users/cohen/GitHub/ruvnet/RuView/rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/ui",
-  "context": {},
-  "metrics": {
-    "edits": 14,
-    "commands": 0,
-    "tasks": 0,
-    "errors": 0
-  }
-}

scripts/gcloud-train.sh

@@ -263,7 +263,7 @@ export LIBTORCH=\$(python3 -c "import torch; print(torch.__path__[0] + '/lib')")
 export LD_LIBRARY_PATH="\${LIBTORCH}:\${LD_LIBRARY_PATH:-}"
 
 # Build the training binary with tch-backend
-cd ~/wifi-densepose/rust-port/wifi-densepose-rs
+cd ~/wifi-densepose/v2
 echo "Building with LIBTORCH=\$LIBTORCH ..."
 cargo build --release --features tch-backend --bin train 2>&1 | tail -5
 
@@ -325,7 +325,7 @@ set -euo pipefail
 source \$HOME/.cargo/env
 export LIBTORCH=\$(python3 -c \"import torch; print(torch.__path__[0] + '/lib')\")
 export LD_LIBRARY_PATH=\"\${LIBTORCH}:\${LD_LIBRARY_PATH:-}\"
-cd ~/wifi-densepose/rust-port/wifi-densepose-rs
+cd ~/wifi-densepose/v2
 
 # Set auto-shutdown timer (safety net)
 sudo shutdown -P +$((MAX_HOURS * 60)) &
@@ -408,7 +408,7 @@ mkdir -p "$LOCAL_RESULTS"
 
 # Package results on the VM
 gcloud compute ssh "$INSTANCE_NAME" --zone="$ZONE" --command="
-cd ~/wifi-densepose/rust-port/wifi-densepose-rs
+cd ~/wifi-densepose/v2
 tar czf ~/training-artifacts.tar.gz \
     checkpoints/ \
     logs/ \

scripts/generate-witness-bundle.sh

@@ -60,7 +60,7 @@ with open('$BUNDLE_DIR/proof/reference_signal_metadata.json', 'w') as f:
 # ---------------------------------------------------------------
 echo "[3/7] Running Rust test suite..."
 mkdir -p "$BUNDLE_DIR/test-results"
-cd "$REPO_ROOT/rust-port/wifi-densepose-rs"
+cd "$REPO_ROOT/v2"
 cargo test --workspace --no-default-features 2>&1 | tee "$BUNDLE_DIR/test-results/rust-workspace-tests.log" | tail -5
 # Extract summary
 grep "^test result" "$BUNDLE_DIR/test-results/rust-workspace-tests.log" | \
@@ -98,7 +98,7 @@ fi
 # ---------------------------------------------------------------
 echo "[6/7] Generating crate manifest..."
 mkdir -p "$BUNDLE_DIR/crate-manifest"
-for crate_dir in "$REPO_ROOT/rust-port/wifi-densepose-rs/crates/"*/; do
+for crate_dir in "$REPO_ROOT/v2/crates/"*/; do
   crate_name="$(basename "$crate_dir")"
   if [ -f "$crate_dir/Cargo.toml" ]; then
     version=$(grep '^version' "$crate_dir/Cargo.toml" | head -1 | sed 's/.*"\(.*\)".*/\1/')

scripts/qemu-mesh-test.sh

@@ -82,7 +82,7 @@ PROJECT_ROOT="$(cd "$SCRIPT_DIR/.." && pwd)"
 
 FIRMWARE_DIR="$PROJECT_ROOT/firmware/esp32-csi-node"
 BUILD_DIR="$FIRMWARE_DIR/build"
-RUST_DIR="$PROJECT_ROOT/rust-port/wifi-densepose-rs"
+RUST_DIR="$PROJECT_ROOT/v2"
 PROVISION_SCRIPT="$FIRMWARE_DIR/provision.py"
 VALIDATE_SCRIPT="$SCRIPT_DIR/validate_mesh_test.py"
 

scripts/qemu_swarm.py

@@ -46,7 +46,7 @@ except ImportError:
 SCRIPT_DIR = Path(__file__).resolve().parent
 PROJECT_ROOT = SCRIPT_DIR.parent
 FIRMWARE_DIR = PROJECT_ROOT / "firmware" / "esp32-csi-node"
-RUST_DIR = PROJECT_ROOT / "rust-port" / "wifi-densepose-rs"
+RUST_DIR = PROJECT_ROOT / "v2" / "wifi-densepose-rs"
 PROVISION_SCRIPT = FIRMWARE_DIR / "provision.py"
 PRESETS_DIR = SCRIPT_DIR / "swarm_presets"
 

ui/README.md

@@ -125,7 +125,7 @@ Open http://localhost:3000/ui/index.html
 
 ### With local Rust binary
 ```bash
-cd rust-port/wifi-densepose-rs
+cd v2
 cargo build -p wifi-densepose-sensing-server --no-default-features
 
 # Run with simulated data

v1/README.md

@@ -51,4 +51,4 @@ pytest tests/
 
 ## Note
 
-This is the legacy Python implementation. For the new Rust implementation with improved performance, see `/rust-port/wifi-densepose-rs/`.
+This is the legacy Python implementation. For the new Rust implementation with improved performance, see `/v2/`.

v2/.claude-flow/daemon-state.json

@@ -64,8 +64,8 @@
   },
   "config": {
     "autoStart": false,
-    "logDir": "/home/user/wifi-densepose/rust-port/wifi-densepose-rs/.claude-flow/logs",
-    "stateFile": "/home/user/wifi-densepose/rust-port/wifi-densepose-rs/.claude-flow/daemon-state.json",
+    "logDir": "/home/user/wifi-densepose/v2/.claude-flow/logs",
+    "stateFile": "/home/user/wifi-densepose/v2/.claude-flow/daemon-state.json",
     "maxConcurrent": 2,
     "workerTimeoutMs": 300000,
     "resourceThresholds": {

v2/.claude-flow/metrics/codebase-map.json

@@ -1,6 +1,6 @@
 {
   "timestamp": "2026-02-28T14:40:51.151Z",
-  "projectRoot": "/home/user/wifi-densepose/rust-port/wifi-densepose-rs",
+  "projectRoot": "/home/user/wifi-densepose/v2",
   "structure": {
     "hasPackageJson": false,
     "hasTsConfig": false,

v2/crates/README.md

@@ -213,7 +213,7 @@ cargo run -p wifi-densepose-train --features tch-backend --bin verify-training
 ```bash
 # Clone the repository
 git clone https://github.com/ruvnet/wifi-densepose.git
-cd wifi-densepose/rust-port/wifi-densepose-rs
+cd wifi-densepose/v2
 
 # Check workspace (no GPU dependencies)
 cargo check --workspace --no-default-features

v2/crates/ruv-neural/README.md

@@ -214,7 +214,7 @@ All crates are published on [crates.io](https://crates.io/search?q=ruv-neural):
 ### Build
 
 ```bash
-cd rust-port/wifi-densepose-rs/crates/ruv-neural
+cd v2/crates/ruv-neural
 cargo build --workspace
 cargo test --workspace
 ```