feat: Add wifi-Mat disaster detection enhancements
Implement 6 optional enhancements for the wifi-Mat module: 1. Hardware Integration (csi_receiver.rs + hardware_adapter.rs) - ESP32 CSI support via serial/UDP - Intel 5300 BFEE file parsing - Atheros CSI Tool integration - Live UDP packet streaming - PCAP replay capability 2. CLI Commands (wifi-densepose-cli/src/mat.rs) - `wifi-mat scan` - Run disaster detection scan - `wifi-mat status` - Check event status - `wifi-mat zones` - Manage scan zones - `wifi-mat survivors` - List detected survivors - `wifi-mat alerts` - View and acknowledge alerts - `wifi-mat export` - Export data in various formats 3. REST API (wifi-densepose-mat/src/api/) - Full CRUD for disaster events - Zone management endpoints - Survivor and alert queries - WebSocket streaming for real-time updates - Comprehensive DTOs and error handling 4. WASM Build (wifi-densepose-wasm/src/mat.rs) - Browser-based disaster dashboard - Real-time survivor tracking - Zone visualization - Alert management - JavaScript API bindings 5. Detection Benchmarks (benches/detection_bench.rs) - Single survivor detection - Multi-survivor detection - Full pipeline benchmarks - Signal processing benchmarks - Hardware adapter benchmarks 6. ML Models for Debris Penetration (ml/) - DebrisModel for material analysis - VitalSignsClassifier for triage - FFT-based feature extraction - Bandpass filtering - Monte Carlo dropout for uncertainty All 134 unit tests pass. Compilation verified for: - wifi-densepose-mat - wifi-densepose-cli - wifi-densepose-wasm (with mat feature)
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Claude
@@ -1,6 +1,10 @@
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//! Detection pipeline combining all vital signs detectors.
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//!
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//! This module provides both traditional signal-processing-based detection
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//! and optional ML-enhanced detection for improved accuracy.
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use crate::domain::{ScanZone, VitalSignsReading, ConfidenceScore};
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use crate::ml::{MlDetectionConfig, MlDetectionPipeline, MlDetectionResult};
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use crate::{DisasterConfig, MatError};
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use super::{
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BreathingDetector, BreathingDetectorConfig,
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@@ -23,6 +27,10 @@ pub struct DetectionConfig {
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pub enable_heartbeat: bool,
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/// Minimum overall confidence to report detection
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pub min_confidence: f64,
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/// Enable ML-enhanced detection
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pub enable_ml: bool,
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/// ML detection configuration (if enabled)
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pub ml_config: Option<MlDetectionConfig>,
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}
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impl Default for DetectionConfig {
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@@ -34,6 +42,8 @@ impl Default for DetectionConfig {
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sample_rate: 1000.0,
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enable_heartbeat: false,
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min_confidence: 0.3,
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enable_ml: false,
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ml_config: None,
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}
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}
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}
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@@ -53,6 +63,20 @@ impl DetectionConfig {
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detection_config
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}
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/// Enable ML-enhanced detection with the given configuration
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pub fn with_ml(mut self, ml_config: MlDetectionConfig) -> Self {
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self.enable_ml = true;
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self.ml_config = Some(ml_config);
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self
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}
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/// Enable ML-enhanced detection with default configuration
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pub fn with_default_ml(mut self) -> Self {
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self.enable_ml = true;
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self.ml_config = Some(MlDetectionConfig::default());
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self
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}
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}
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/// Trait for vital signs detection
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@@ -123,20 +147,42 @@ pub struct DetectionPipeline {
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heartbeat_detector: HeartbeatDetector,
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movement_classifier: MovementClassifier,
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data_buffer: parking_lot::RwLock<CsiDataBuffer>,
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/// Optional ML detection pipeline
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ml_pipeline: Option<MlDetectionPipeline>,
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}
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impl DetectionPipeline {
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/// Create a new detection pipeline
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pub fn new(config: DetectionConfig) -> Self {
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let ml_pipeline = if config.enable_ml {
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config.ml_config.clone().map(MlDetectionPipeline::new)
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} else {
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None
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};
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Self {
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breathing_detector: BreathingDetector::new(config.breathing.clone()),
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heartbeat_detector: HeartbeatDetector::new(config.heartbeat.clone()),
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movement_classifier: MovementClassifier::new(config.movement.clone()),
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data_buffer: parking_lot::RwLock::new(CsiDataBuffer::new(config.sample_rate)),
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ml_pipeline,
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config,
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}
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}
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/// Initialize ML models asynchronously (if enabled)
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pub async fn initialize_ml(&mut self) -> Result<(), MatError> {
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if let Some(ref mut ml) = self.ml_pipeline {
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ml.initialize().await.map_err(MatError::from)?;
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}
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Ok(())
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}
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/// Check if ML pipeline is ready
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pub fn ml_ready(&self) -> bool {
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self.ml_pipeline.as_ref().map_or(true, |ml| ml.is_ready())
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}
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/// Process a scan zone and return detected vital signs
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pub async fn process_zone(&self, zone: &ScanZone) -> Result<Option<VitalSignsReading>, MatError> {
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// In a real implementation, this would:
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@@ -152,17 +198,66 @@ impl DetectionPipeline {
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return Ok(None);
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}
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// Detect vital signs
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// Detect vital signs using traditional pipeline
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let reading = self.detect_from_buffer(&buffer, zone)?;
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// If ML is enabled and ready, enhance with ML predictions
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let enhanced_reading = if self.config.enable_ml && self.ml_ready() {
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self.enhance_with_ml(reading, &buffer).await?
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} else {
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reading
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};
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// Check minimum confidence
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if let Some(ref r) = reading {
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if let Some(ref r) = enhanced_reading {
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if r.confidence.value() < self.config.min_confidence {
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return Ok(None);
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}
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}
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Ok(reading)
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Ok(enhanced_reading)
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}
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/// Enhance detection results with ML predictions
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async fn enhance_with_ml(
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&self,
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traditional_reading: Option<VitalSignsReading>,
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buffer: &CsiDataBuffer,
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) -> Result<Option<VitalSignsReading>, MatError> {
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let ml_pipeline = match &self.ml_pipeline {
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Some(ml) => ml,
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None => return Ok(traditional_reading),
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};
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// Get ML predictions
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let ml_result = ml_pipeline.process(buffer).await.map_err(MatError::from)?;
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// If we have ML vital classification, use it to enhance or replace traditional
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if let Some(ref ml_vital) = ml_result.vital_classification {
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if let Some(vital_reading) = ml_vital.to_vital_signs_reading() {
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// If ML result has higher confidence, prefer it
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if let Some(ref traditional) = traditional_reading {
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if ml_result.overall_confidence() > traditional.confidence.value() as f32 {
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return Ok(Some(vital_reading));
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}
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} else {
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// No traditional reading, use ML result
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return Ok(Some(vital_reading));
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}
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}
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}
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Ok(traditional_reading)
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}
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/// Get the latest ML detection results (if ML is enabled)
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pub async fn get_ml_results(&self) -> Option<MlDetectionResult> {
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let buffer = self.data_buffer.read();
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if let Some(ref ml) = self.ml_pipeline {
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ml.process(&buffer).await.ok()
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} else {
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None
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}
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}
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/// Add CSI data to the processing buffer
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@@ -236,8 +331,23 @@ impl DetectionPipeline {
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self.breathing_detector = BreathingDetector::new(config.breathing.clone());
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self.heartbeat_detector = HeartbeatDetector::new(config.heartbeat.clone());
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self.movement_classifier = MovementClassifier::new(config.movement.clone());
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// Update ML pipeline if configuration changed
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if config.enable_ml != self.config.enable_ml || config.ml_config != self.config.ml_config {
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self.ml_pipeline = if config.enable_ml {
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config.ml_config.clone().map(MlDetectionPipeline::new)
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} else {
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None
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};
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}
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self.config = config;
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}
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/// Get the ML pipeline (if enabled)
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pub fn ml_pipeline(&self) -> Option<&MlDetectionPipeline> {
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self.ml_pipeline.as_ref()
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}
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}
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impl VitalSignsDetector for DetectionPipeline {
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