# Functional Specification ## WiFi-DensePose System ### Document Information - **Version**: 1.0 - **Date**: 2025-01-07 - **Project**: InvisPose - WiFi-Based Dense Human Pose Estimation - **Status**: Draft --- ## 1. Introduction ### 1.1 Purpose This document defines the functional requirements and behaviors of the WiFi-DensePose system, specifying what the system must do to meet user needs across healthcare, retail, and security domains. ### 1.2 Scope The functional specification covers all user-facing features, system behaviors, data processing workflows, and integration capabilities required for the WiFi-based human pose estimation platform. ### 1.3 Functional Overview The system transforms WiFi Channel State Information (CSI) into real-time human pose estimates through neural network processing, providing privacy-preserving human sensing capabilities with 87.2% accuracy. --- ## 2. Core Functional Requirements ### 2.1 CSI Data Collection and Processing #### 2.1.1 WiFi Signal Acquisition **Function**: Extract Channel State Information from compatible WiFi routers - **Input**: Raw WiFi signals from 3×3 MIMO antenna arrays - **Processing**: Real-time CSI extraction with amplitude and phase data - **Output**: Structured CSI data streams with temporal coherence - **Frequency**: Continuous operation at 10-30 Hz sampling rate **Acceptance Criteria**: - Successfully extract CSI from Atheros-based routers - Maintain data integrity across extended operation periods - Handle network interruptions with automatic reconnection - Support multiple router types with unified data format #### 2.1.2 Signal Preprocessing **Function**: Clean and normalize raw CSI data for neural network input - **Phase Unwrapping**: Correct phase discontinuities and wrapping artifacts - **Temporal Filtering**: Apply moving average and linear detrending - **Background Subtraction**: Remove static environmental components - **Noise Reduction**: Filter systematic noise and interference **Processing Pipeline**: ``` Raw CSI → Phase Unwrapping → Temporal Filtering → Background Subtraction → Noise Reduction → Normalized CSI ``` **Acceptance Criteria**: - Achieve signal-to-noise ratio improvement of 10dB minimum - Maintain temporal coherence across processing stages - Adapt to environmental changes automatically - Process data streams without introducing latency >10ms #### 2.1.3 Environmental Calibration **Function**: Establish baseline measurements for background subtraction - **Baseline Capture**: Record empty environment CSI patterns - **Adaptive Calibration**: Update baselines for environmental changes - **Multi-Environment**: Support different room configurations - **Drift Compensation**: Correct for systematic signal drift **Calibration Process**: 1. Capture 60-second baseline with no human presence 2. Establish statistical models for background variation 3. Monitor for environmental changes requiring recalibration 4. Update baselines automatically or on user request ### 2.2 Neural Network Inference #### 2.2.1 Modality Translation Network **Function**: Convert 1D CSI signals to 2D spatial representations - **Dual-Branch Processing**: Separate amplitude and phase encoders - **Feature Fusion**: Combine modality-specific features - **Spatial Upsampling**: Generate 720×1280 spatial representations - **Temporal Consistency**: Maintain coherence across frames **Network Architecture**: ``` CSI Input (3×3×N) → Amplitude Branch → Feature Fusion → Phase Branch → Upsampling → Spatial Features (720×1280×3) ``` **Performance Requirements**: - Processing latency <50ms on GPU hardware - Maintain temporal consistency across frame sequences - Support batch processing for efficiency - Graceful degradation on CPU-only systems #### 2.2.2 DensePose Estimation **Function**: Extract dense human pose from spatial features - **Body Part Detection**: Identify 24 anatomical regions - **UV Coordinate Mapping**: Generate dense correspondence maps - **Keypoint Extraction**: Detect 17 major body keypoints - **Confidence Scoring**: Provide detection confidence metrics **Output Format**: - Dense pose masks for 24 body parts - UV coordinates for surface mapping - 2D keypoint coordinates with confidence scores - Bounding boxes for detected persons #### 2.2.3 Multi-Person Tracking **Function**: Track multiple individuals across frame sequences - **Person Detection**: Identify up to 5 individuals simultaneously - **ID Assignment**: Maintain consistent person identifiers - **Occlusion Handling**: Track through temporary occlusions - **Trajectory Smoothing**: Apply temporal filtering for stability **Tracking Features**: - Kalman filtering for position prediction - Hungarian algorithm for ID assignment - Confidence-based track management - Automatic track initialization and termination ### 2.3 Real-Time Processing Pipeline #### 2.3.1 Data Flow Management **Function**: Orchestrate end-to-end processing pipeline - **Buffer Management**: Handle continuous data streams - **Queue Processing**: Manage processing queues efficiently - **Resource Allocation**: Optimize CPU/GPU utilization - **Error Recovery**: Handle processing failures gracefully **Pipeline Stages**: 1. CSI Data Ingestion 2. Preprocessing and Normalization 3. Neural Network Inference 4. Post-processing and Tracking 5. Output Generation and Distribution #### 2.3.2 Performance Optimization **Function**: Maintain real-time performance under varying loads - **Adaptive Processing**: Scale processing based on available resources - **Frame Dropping**: Skip frames under high load conditions - **Batch Optimization**: Group operations for efficiency - **Memory Management**: Prevent memory leaks and optimize usage **Optimization Strategies**: - Dynamic batch size adjustment - GPU memory pooling - Asynchronous processing pipelines - Intelligent frame scheduling --- ## 3. User Stories and Use Cases ### 3.1 Healthcare Domain User Stories #### 3.1.1 Elderly Care Monitoring **As a** healthcare provider **I want** to monitor elderly patients for fall events and activity patterns **So that** I can provide immediate assistance and track health trends **Acceptance Criteria**: - System detects falls with 95% accuracy within 2 seconds - Activity patterns are tracked and reported daily - Alerts are sent immediately upon fall detection - Privacy is maintained with no video recording **User Journey**: 1. Caregiver configures fall detection sensitivity 2. System continuously monitors patient movement 3. Fall event triggers immediate alert to caregiver 4. System provides activity summary for health assessment // TEST: Verify fall detection accuracy meets 95% threshold // TEST: Confirm activity tracking provides meaningful health insights // TEST: Validate alert delivery within 2-second requirement #### 3.1.2 Rehabilitation Progress Tracking **As a** physical therapist **I want** to track patient movement and exercise compliance **So that** I can adjust treatment plans based on objective data **Acceptance Criteria**: - Exercise movements are accurately classified - Progress metrics are calculated and visualized - Compliance rates are tracked over time - Integration with electronic health records **User Journey**: 1. Therapist sets up exercise monitoring protocol 2. Patient performs prescribed exercises 3. System tracks movement quality and completion 4. Progress reports are generated for treatment planning // TEST: Verify exercise classification accuracy for rehabilitation movements // TEST: Confirm progress metrics calculation and visualization // TEST: Validate EHR integration functionality ### 3.2 Retail Domain User Stories #### 3.2.1 Store Layout Optimization **As a** retail manager **I want** to understand customer traffic patterns and zone popularity **So that** I can optimize store layout and product placement **Acceptance Criteria**: - Customer paths are tracked anonymously - Zone dwell times are measured accurately - Heatmaps show traffic density patterns - A/B testing capabilities for layout changes **User Journey**: 1. Manager configures store zones and tracking areas 2. System monitors customer movement throughout day 3. Analytics dashboard shows traffic patterns and insights 4. Manager uses data to optimize store layout // TEST: Verify anonymous customer tracking maintains privacy // TEST: Confirm zone analytics provide actionable insights // TEST: Validate A/B testing framework for layout optimization #### 3.2.2 Queue Management **As a** store operations manager **I want** to monitor checkout queue lengths and wait times **So that** I can optimize staffing and reduce customer wait times **Acceptance Criteria**: - Queue lengths are detected in real-time - Wait times are calculated automatically - Staff alerts when queues exceed thresholds - Historical data for staffing optimization **User Journey**: 1. Manager sets queue length and wait time thresholds 2. System monitors checkout areas continuously 3. Alerts are sent when thresholds are exceeded 4. Historical data guides staffing decisions // TEST: Verify queue detection accuracy in various store layouts // TEST: Confirm wait time calculations are precise // TEST: Validate alert system for queue management ### 3.3 Security Domain User Stories #### 3.3.1 Perimeter Security Monitoring **As a** security officer **I want** to monitor restricted areas for unauthorized access **So that** I can respond quickly to security breaches **Acceptance Criteria**: - Intrusion detection works through walls and obstacles - Real-time alerts with location information - Integration with existing security systems - Audit trail for all security events **User Journey**: 1. Security officer configures restricted zones 2. System monitors areas 24/7 without line-of-sight 3. Intrusion triggers immediate alert with location 4. Officer responds based on alert information // TEST: Verify through-wall detection capability // TEST: Confirm real-time alert delivery with accurate location // TEST: Validate integration with security management systems #### 3.3.2 Building Occupancy Monitoring **As a** facility manager **I want** to track building occupancy for safety and compliance **So that** I can ensure emergency evacuation procedures and capacity limits **Acceptance Criteria**: - Accurate person counting in all monitored areas - Real-time occupancy dashboard - Emergency evacuation support - Compliance reporting for safety regulations **User Journey**: 1. Manager configures occupancy limits for each area 2. System tracks person count continuously 3. Dashboard shows real-time occupancy status 4. Emergency mode provides evacuation support // TEST: Verify person counting accuracy across different environments // TEST: Confirm occupancy dashboard provides real-time updates // TEST: Validate emergency evacuation support functionality --- ## 4. Real-Time Streaming Requirements ### 4.1 Performance Requirements #### 4.1.1 Latency Requirements **End-to-End Latency**: <100ms from CSI data to pose output - CSI Processing: <20ms - Neural Network Inference: <50ms - Post-processing and Tracking: <20ms - API Response Generation: <10ms **Streaming Latency**: <50ms for WebSocket delivery - Internal Processing: <30ms - Network Transmission: <20ms // TEST: Verify end-to-end latency meets <100ms requirement // TEST: Confirm WebSocket streaming latency <50ms // TEST: Validate latency consistency under varying loads #### 4.1.2 Throughput Requirements **Processing Throughput**: 10-30 FPS depending on hardware - Minimum: 10 FPS on CPU-only systems - Optimal: 20 FPS on GPU-accelerated systems - Maximum: 30 FPS on high-end hardware **Concurrent Streaming**: Support 100+ simultaneous clients - WebSocket connections: 100 concurrent - REST API clients: 1000 concurrent - Streaming bandwidth: 10 Mbps per client // TEST: Verify processing throughput meets FPS requirements // TEST: Confirm system supports 100+ concurrent streaming clients // TEST: Validate bandwidth utilization stays within limits ### 4.2 Data Streaming Architecture #### 4.2.1 Multi-Protocol Support **WebSocket Streaming**: Primary real-time protocol - Binary and JSON message formats - Compression for bandwidth optimization - Automatic reconnection handling - Client-side buffering for smooth playback **Server-Sent Events (SSE)**: Alternative streaming protocol - HTTP-based streaming for firewall compatibility - Automatic retry and reconnection - Event-based message delivery - Browser-native support **MQTT Streaming**: IoT ecosystem integration - QoS levels for reliability guarantees - Topic-based message routing - Retained messages for state persistence - Scalable pub/sub architecture // TEST: Verify WebSocket streaming handles reconnections gracefully // TEST: Confirm SSE provides reliable alternative streaming // TEST: Validate MQTT integration with IoT ecosystems #### 4.2.2 Adaptive Streaming **Quality Adaptation**: Automatic quality adjustment based on network conditions - Bandwidth detection and monitoring - Dynamic frame rate adjustment - Compression level optimization - Graceful degradation strategies **Client Capability Detection**: Optimize streaming for client capabilities - Device performance assessment - Network bandwidth measurement - Display resolution adaptation - Battery optimization for mobile clients // TEST: Verify adaptive streaming adjusts to network conditions // TEST: Confirm client capability detection works accurately // TEST: Validate quality adaptation maintains user experience ### 4.3 Restream Integration Specifications #### 4.3.1 Platform Support **Supported Platforms**: Multi-platform simultaneous streaming - YouTube Live: RTMP streaming with custom overlays - Twitch: Real-time pose visualization streams - Facebook Live: Social media integration - Custom RTMP: Enterprise and private platforms **Stream Configuration**: Flexible streaming parameters - Resolution: 720p, 1080p, 4K support - Frame Rate: 15, 30, 60 FPS options - Bitrate: Adaptive 1-10 Mbps - Codec: H.264, H.265 support // TEST: Verify simultaneous streaming to multiple platforms // TEST: Confirm stream quality meets platform requirements // TEST: Validate custom RTMP endpoint functionality #### 4.3.2 Visualization Pipeline **Pose Overlay Generation**: Real-time visualization creation - Skeleton rendering with customizable styles - Confidence indicators and person IDs - Background options (transparent, solid, custom) - Multi-person color coding **Stream Composition**: Video stream assembly - Pose overlay compositing - Background image/video integration - Text overlay for metadata - Logo and branding integration **Performance Optimization**: Efficient video processing - GPU-accelerated rendering - Parallel processing pipelines - Memory-efficient operations - Real-time encoding optimization // TEST: Verify pose overlay generation meets quality standards // TEST: Confirm stream composition handles multiple elements // TEST: Validate performance optimization maintains real-time processing #### 4.3.3 Stream Management **Connection Management**: Robust streaming infrastructure - Automatic reconnection on failures - Stream health monitoring - Bandwidth adaptation - Error recovery procedures **Analytics and Monitoring**: Stream performance tracking - Viewer count monitoring - Stream quality metrics - Bandwidth utilization tracking - Error rate monitoring **Configuration Management**: Dynamic stream control - Real-time parameter adjustment - Stream start/stop control - Platform-specific optimizations - Scheduled streaming support // TEST: Verify stream management handles connection failures // TEST: Confirm analytics provide meaningful insights // TEST: Validate configuration changes apply without interruption --- ## 5. Domain-Specific Functional Requirements ### 3.1 Healthcare Monitoring #### 3.1.1 Fall Detection **Function**: Detect and alert on fall events for elderly care - **Pattern Recognition**: Identify rapid position changes - **Threshold Configuration**: Adjustable sensitivity settings - **Alert Generation**: Immediate notification on fall detection - **False Positive Reduction**: Filter normal activities **Detection Algorithm**: ``` Pose Trajectory Analysis → Velocity Calculation → Position Change Detection → Confidence Assessment → Alert Decision ``` **Alert Criteria**: - Vertical position change >1.5m in <2 seconds - Horizontal impact detection - Sustained ground-level position >10 seconds - Configurable sensitivity thresholds #### 3.1.2 Activity Monitoring **Function**: Track patient mobility and activity patterns - **Activity Classification**: Identify sitting, standing, walking, lying - **Mobility Metrics**: Calculate movement frequency and duration - **Inactivity Detection**: Alert on prolonged inactivity periods - **Daily Reports**: Generate activity summaries **Monitored Activities**: - Walking patterns and gait analysis - Sitting/standing transitions - Sleep position monitoring - Exercise and rehabilitation activities #### 3.1.3 Privacy-Preserving Analytics **Function**: Generate health insights while protecting patient privacy - **Anonymous Data**: No personally identifiable information - **Aggregated Metrics**: Statistical summaries only - **Secure Storage**: Encrypted local data storage - **Audit Trails**: Comprehensive access logging ### 3.2 Retail Analytics #### 3.2.1 Customer Traffic Analysis **Function**: Monitor customer movement and behavior patterns - **Traffic Counting**: Real-time customer count tracking - **Zone Analytics**: Movement between store zones - **Dwell Time**: Time spent in specific areas - **Path Analysis**: Customer journey mapping **Analytics Outputs**: - Hourly/daily traffic reports - Zone popularity heatmaps - Average dwell time by area - Peak traffic period identification #### 3.2.2 Occupancy Management **Function**: Monitor store capacity and density - **Real-Time Counts**: Current occupancy levels - **Capacity Alerts**: Notifications at threshold levels - **Queue Detection**: Identify waiting areas and lines - **Social Distancing**: Monitor spacing compliance **Capacity Features**: - Configurable occupancy limits - Real-time dashboard displays - Automated alert systems - Historical occupancy trends #### 3.2.3 Layout Optimization **Function**: Provide insights for store layout improvements - **Traffic Flow**: Identify bottlenecks and dead zones - **Product Interaction**: Monitor engagement with displays - **Conversion Analysis**: Path-to-purchase tracking - **A/B Testing**: Compare layout configurations ### 3.3 Security Applications #### 3.3.1 Intrusion Detection **Function**: Monitor restricted areas for unauthorized access - **Perimeter Monitoring**: Detect boundary crossings - **Through-Wall Detection**: Monitor without line-of-sight - **Behavioral Analysis**: Identify suspicious movement patterns - **Real-Time Alerts**: Immediate security notifications **Detection Capabilities**: - Motion detection in restricted zones - Loitering detection with configurable timeouts - Multiple person alerts - Integration with security systems #### 3.3.2 Access Control Integration **Function**: Enhance physical security systems - **Zone-Based Monitoring**: Different security levels by area - **Time-Based Rules**: Schedule-dependent monitoring - **Credential Correlation**: Link with access card systems - **Audit Logging**: Comprehensive security event logs #### 3.3.3 Emergency Response **Function**: Support emergency evacuation and response - **Occupancy Tracking**: Real-time person counts by zone - **Evacuation Monitoring**: Track movement during emergencies - **First Responder Support**: Provide occupancy information - **Emergency Alerts**: Automated emergency notifications --- ## 4. API and Integration Functions ### 4.1 REST API Endpoints #### 4.1.1 Pose Data Access **Endpoints**: - `GET /pose/latest` - Current pose data - `GET /pose/history` - Historical pose data - `GET /pose/stream` - Real-time pose stream - `POST /pose/query` - Custom pose queries **Response Format**: ```json { "timestamp": "2025-01-07T04:46:32Z", "persons": [ { "id": 1, "confidence": 0.87, "keypoints": [...], "dense_pose": {...}, "bounding_box": {...} } ], "metadata": { "processing_time": 45, "frame_id": 12345 } } ``` #### 4.1.2 System Control **Endpoints**: - `POST /system/start` - Start pose estimation - `POST /system/stop` - Stop pose estimation - `GET /system/status` - System health status - `POST /system/calibrate` - Trigger calibration #### 4.1.3 Configuration Management **Endpoints**: - `GET /config` - Current configuration - `PUT /config` - Update configuration - `GET /config/templates` - Available templates - `POST /config/validate` - Validate configuration ### 4.2 WebSocket Streaming #### 4.2.1 Real-Time Data Streams **Function**: Provide low-latency pose data streaming - **Connection Management**: Handle multiple concurrent clients - **Message Broadcasting**: Efficient data distribution - **Automatic Reconnection**: Client reconnection handling - **Rate Limiting**: Prevent client overload **Stream Types**: - Pose data streams - System status updates - Alert notifications - Performance metrics #### 4.2.2 Client Management **Function**: Manage WebSocket client lifecycle - **Authentication**: Secure client connections - **Subscription Management**: Topic-based subscriptions - **Connection Monitoring**: Health check and cleanup - **Error Handling**: Graceful error recovery ### 4.3 External Integration #### 4.3.1 MQTT Publishing **Function**: Integrate with IoT ecosystems - **Topic Structure**: Hierarchical topic organization - **Message Formats**: JSON and binary message support - **QoS Levels**: Configurable quality of service - **Retained Messages**: State persistence **MQTT Topics**: - `wifi-densepose/pose/person/{id}` - Individual pose data - `wifi-densepose/alerts/{type}` - Alert notifications - `wifi-densepose/status` - System status - `wifi-densepose/analytics/{domain}` - Domain analytics #### 4.3.2 Webhook Integration **Function**: Send real-time notifications to external services - **Event Triggers**: Configurable event conditions - **Retry Logic**: Automatic retry on failures - **Authentication**: Support for various auth methods - **Payload Customization**: Flexible message formats **Webhook Events**: - Person detection/departure - Fall detection alerts - System status changes - Threshold violations #### 4.3.3 Restream Integration **Function**: Live streaming to multiple platforms - **Multi-Platform**: Simultaneous streaming to multiple services - **Video Encoding**: Real-time video generation - **Stream Management**: Automatic reconnection and quality adaptation - **Overlay Generation**: Pose visualization overlays --- ## 5. User Interface Functions ### 5.1 Web Dashboard #### 5.1.1 Real-Time Visualization **Function**: Display live pose estimation results - **Pose Rendering**: Real-time skeleton visualization - **Multi-Person Display**: Color-coded person tracking - **Confidence Indicators**: Visual confidence representation - **Background Options**: Configurable visualization backgrounds **Visualization Features**: - Stick figure pose representation - Dense pose heat maps - Keypoint confidence visualization - Trajectory tracking displays #### 5.1.2 System Monitoring **Function**: Monitor system health and performance - **Performance Metrics**: Real-time performance indicators - **Resource Usage**: CPU, GPU, memory utilization - **Network Status**: CSI data stream health - **Error Reporting**: System error and warning displays #### 5.1.3 Configuration Interface **Function**: System configuration and control - **Parameter Adjustment**: Real-time parameter tuning - **Template Selection**: Domain-specific configuration templates - **Calibration Control**: Manual calibration triggers - **Alert Configuration**: Threshold and notification settings ### 5.2 Mobile Interface #### 5.2.1 Responsive Design **Function**: Mobile-optimized interface for monitoring - **Touch Interface**: Mobile-friendly controls - **Responsive Layout**: Adaptive screen sizing - **Offline Capability**: Basic functionality without connectivity - **Push Notifications**: Mobile alert delivery #### 5.2.2 Quick Actions **Function**: Essential controls for mobile users - **System Start/Stop**: Basic system control - **Alert Acknowledgment**: Quick alert responses - **Status Overview**: System health summary - **Emergency Controls**: Rapid emergency response --- ## 6. Data Management Functions ### 6.1 Data Storage #### 6.1.1 Pose Data Storage **Function**: Store pose estimation results for analysis - **Time-Series Storage**: Efficient temporal data storage - **Compression**: Data compression for storage efficiency - **Indexing**: Fast query performance - **Retention Policies**: Configurable data retention **Storage Schema**: ``` pose_data: - timestamp (primary key) - person_id - pose_keypoints - confidence_scores - metadata ``` #### 6.1.2 Configuration Storage **Function**: Persist system configuration and settings - **Version Control**: Configuration change tracking - **Backup/Restore**: Configuration backup capabilities - **Template Management**: Pre-configured templates - **Validation**: Configuration integrity checking #### 6.1.3 Analytics Storage **Function**: Store aggregated analytics and reports - **Domain-Specific**: Separate storage for different domains - **Aggregation**: Pre-computed analytics for performance - **Export Capabilities**: Data export in multiple formats - **Privacy Compliance**: Anonymized data storage ### 6.2 Data Processing #### 6.2.1 Batch Analytics **Function**: Process historical data for insights - **Trend Analysis**: Long-term pattern identification - **Statistical Analysis**: Comprehensive statistical metrics - **Report Generation**: Automated report creation - **Data Mining**: Advanced pattern discovery #### 6.2.2 Real-Time Analytics **Function**: Generate live insights from streaming data - **Stream Processing**: Real-time data aggregation - **Threshold Monitoring**: Live threshold violation detection - **Anomaly Detection**: Real-time anomaly identification - **Alert Generation**: Immediate alert processing --- ## 7. Quality Assurance Functions ### 7.1 Testing and Validation #### 7.1.1 Automated Testing **Function**: Comprehensive automated test coverage - **Unit Testing**: Component-level test coverage - **Integration Testing**: End-to-end pipeline testing - **Performance Testing**: Load and stress testing - **Regression Testing**: Continuous validation #### 7.1.2 Hardware Simulation **Function**: Test without physical hardware - **CSI Simulation**: Synthetic CSI data generation - **Scenario Testing**: Predefined test scenarios - **Environment Simulation**: Various deployment conditions - **Validation Testing**: Algorithm validation ### 7.2 Monitoring and Diagnostics #### 7.2.1 System Health Monitoring **Function**: Continuous system health assessment - **Performance Monitoring**: Real-time performance tracking - **Resource Monitoring**: Hardware resource utilization - **Error Detection**: Automatic error identification - **Predictive Maintenance**: Proactive issue identification #### 7.2.2 Diagnostic Tools **Function**: Troubleshooting and problem resolution - **Log Analysis**: Comprehensive log analysis tools - **Performance Profiling**: Detailed performance analysis - **Network Diagnostics**: CSI data stream analysis - **Debug Interfaces**: Developer debugging tools --- ## 8. Acceptance Criteria ### 8.1 Functional Acceptance - **Pose Detection**: Successfully detect human poses with 87.2% AP@50 - **Multi-Person**: Track up to 5 individuals simultaneously - **Real-Time**: Maintain <100ms end-to-end latency - **Domain Functions**: All domain-specific features operational ### 8.2 Integration Acceptance - **API Endpoints**: All specified endpoints functional - **WebSocket Streaming**: Real-time data streaming operational - **External Integration**: MQTT, webhooks, and Restream functional - **Dashboard**: Web interface fully operational ### 8.3 Performance Acceptance - **Throughput**: Achieve 10-30 FPS processing rates - **Reliability**: 99.5% uptime over testing period - **Scalability**: Support 100+ concurrent API clients - **Resource Usage**: Operate within specified hardware limits // TEST: Validate CSI data extraction from all supported router types // TEST: Verify neural network inference accuracy meets AP@50 targets // TEST: Confirm multi-person tracking maintains ID consistency // TEST: Validate real-time performance under various load conditions // TEST: Test all API endpoints for correct functionality // TEST: Verify WebSocket streaming handles multiple concurrent clients // TEST: Validate domain-specific functions for healthcare, retail, security // TEST: Confirm external integrations work with MQTT, webhooks, Restream // TEST: Test web dashboard functionality across different browsers // TEST: Validate data storage and retrieval operations // TEST: Verify system monitoring and diagnostic capabilities // TEST: Confirm automated testing framework covers all components