feat(ruvector): implement ADR-017 as wifi-densepose-ruvector crate + fix MAT warnings

New crate `wifi-densepose-ruvector` implements all 7 ruvector v2.0.4
integration points from ADR-017 (signal processing + MAT disaster detection):

signal::subcarrier   — mincut_subcarrier_partition (ruvector-mincut)
signal::spectrogram  — gate_spectrogram (ruvector-attn-mincut)
signal::bvp          — attention_weighted_bvp (ruvector-attention)
signal::fresnel      — solve_fresnel_geometry (ruvector-solver)
mat::triangulation   — solve_triangulation TDoA (ruvector-solver)
mat::breathing       — CompressedBreathingBuffer 50-75% mem reduction (ruvector-temporal-tensor)
mat::heartbeat       — CompressedHeartbeatSpectrogram tiered compression (ruvector-temporal-tensor)

16 tests, 0 compilation errors. Workspace grows from 14 → 15 crates.

MAT crate: fix all 54 warnings (0 remaining in wifi-densepose-mat):
- Remove unused imports (Arc, HashMap, RwLock, mpsc, Mutex, ConfidenceScore, etc.)
- Prefix unused variables with _ (timestamp_low, agc, perm)
- Add #![allow(unexpected_cfgs)] for onnx feature gates in ML files
- Move onnx-conditional imports under #[cfg(feature = "onnx")] guards

README: update crate count 14→15, ADR count 24→26, add ruvector crate
table with 7-row integration summary.

Total tests: 939 → 955 (16 new). All passing, 0 regressions.

https://claude.ai/code/session_0164UZu6rG6gA15HmVyLZAmU

rust-port/wifi-densepose-rs/crates/wifi-densepose-mat/src/detection/breathing.rs

@@ -1,6 +1,6 @@
 //! Breathing pattern detection from CSI signals.
 
-use crate::domain::{BreathingPattern, BreathingType, ConfidenceScore};
+use crate::domain::{BreathingPattern, BreathingType};
 
 // ---------------------------------------------------------------------------
 // Integration 6: CompressedBreathingBuffer (ADR-017, ruvector feature)

rust-port/wifi-densepose-rs/crates/wifi-densepose-mat/src/detection/pipeline.rs

@@ -3,7 +3,7 @@
 //! This module provides both traditional signal-processing-based detection
 //! and optional ML-enhanced detection for improved accuracy.
 
-use crate::domain::{ScanZone, VitalSignsReading, ConfidenceScore};
+use crate::domain::{ScanZone, VitalSignsReading};
 use crate::ml::{MlDetectionConfig, MlDetectionPipeline, MlDetectionResult};
 use crate::{DisasterConfig, MatError};
 use super::{

rust-port/wifi-densepose-rs/crates/wifi-densepose-mat/src/integration/csi_receiver.rs

@@ -28,8 +28,6 @@ use chrono::{DateTime, Utc};
 use std::collections::VecDeque;
 use std::io::{BufReader, Read};
 use std::path::Path;
-use std::sync::Arc;
-use tokio::sync::{mpsc, Mutex};
 
 /// Configuration for CSI receivers
 #[derive(Debug, Clone)]
@@ -921,7 +919,7 @@ impl CsiParser {
         }
 
         // Parse header
-        let timestamp_low = u32::from_le_bytes([data[0], data[1], data[2], data[3]]);
+        let _timestamp_low = u32::from_le_bytes([data[0], data[1], data[2], data[3]]);
         let bfee_count = u16::from_le_bytes([data[4], data[5]]);
         let _nrx = data[8];
         let ntx = data[9];
@@ -929,8 +927,8 @@ impl CsiParser {
         let rssi_b = data[11] as i8;
         let rssi_c = data[12] as i8;
         let noise = data[13] as i8;
-        let agc = data[14];
-        let perm = [data[15], data[16], data[17]];
+        let _agc = data[14];
+        let _perm = [data[15], data[16], data[17]];
         let rate = u16::from_le_bytes([data[18], data[19]]);
 
         // Average RSSI

rust-port/wifi-densepose-rs/crates/wifi-densepose-mat/src/ml/debris_model.rs

@@ -15,14 +15,13 @@
 //! - Attenuation regression head (linear output)
 //! - Depth estimation head with uncertainty (mean + variance output)
 
+#![allow(unexpected_cfgs)]
+
 use super::{DebrisFeatures, DepthEstimate, MlError, MlResult};
-use ndarray::{Array1, Array2, Array4, s};
-use std::collections::HashMap;
+use ndarray::{Array2, Array4};
 use std::path::Path;
-use std::sync::Arc;
-use parking_lot::RwLock;
 use thiserror::Error;
-use tracing::{debug, info, instrument, warn};
+use tracing::{info, instrument, warn};
 
 #[cfg(feature = "onnx")]
 use wifi_densepose_nn::{OnnxBackend, OnnxSession, InferenceOptions, Tensor, TensorShape};

rust-port/wifi-densepose-rs/crates/wifi-densepose-mat/src/ml/mod.rs

@@ -35,9 +35,7 @@ pub use vital_signs_classifier::{
 };
 
 use crate::detection::CsiDataBuffer;
-use crate::domain::{VitalSignsReading, BreathingPattern, HeartbeatSignature};
 use async_trait::async_trait;
-use std::path::Path;
 use thiserror::Error;
 
 /// Errors that can occur in ML operations

rust-port/wifi-densepose-rs/crates/wifi-densepose-mat/src/ml/vital_signs_classifier.rs

@@ -21,18 +21,27 @@
 //!                             [Uncertainty]   [Confidence]    [Voluntary Flag]
 //! ```
 
+#![allow(unexpected_cfgs)]
+
 use super::{MlError, MlResult};
 use crate::detection::CsiDataBuffer;
 use crate::domain::{
     BreathingPattern, BreathingType, HeartbeatSignature, MovementProfile,
     MovementType, SignalStrength, VitalSignsReading,
 };
-use ndarray::{Array1, Array2, Array4, s};
-use std::collections::HashMap;
 use std::path::Path;
+use tracing::{info, instrument, warn};
+
+#[cfg(feature = "onnx")]
+use ndarray::{Array1, Array2, Array4, s};
+#[cfg(feature = "onnx")]
+use std::collections::HashMap;
+#[cfg(feature = "onnx")]
 use std::sync::Arc;
+#[cfg(feature = "onnx")]
 use parking_lot::RwLock;
-use tracing::{debug, info, instrument, warn};
+#[cfg(feature = "onnx")]
+use tracing::debug;
 
 #[cfg(feature = "onnx")]
 use wifi_densepose_nn::{OnnxBackend, OnnxSession, InferenceOptions, Tensor, TensorShape};
@@ -813,7 +822,7 @@ impl VitalSignsClassifier {
     }
 
     /// Compute breathing class probabilities
-    fn compute_breathing_probabilities(&self, rate_bpm: f32, features: &VitalSignsFeatures) -> Vec<f32> {
+    fn compute_breathing_probabilities(&self, rate_bpm: f32, _features: &VitalSignsFeatures) -> Vec<f32> {
         let mut probs = vec![0.0; 6]; // Normal, Shallow, Labored, Irregular, Agonal, Apnea
 
         // Simple probability assignment based on rate