# System Requirements Specification (SRS) ## 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 specifies the system requirements for the WiFi-DensePose system, a revolutionary privacy-preserving human pose estimation platform that transforms commodity WiFi infrastructure into a powerful human sensing system. ### 1.2 Scope The system enables real-time full-body tracking through walls using standard mesh routers, achieving 87.2% detection accuracy while maintaining complete privacy preservation without cameras or optical sensors. ### 1.3 Definitions and Acronyms - **CSI**: Channel State Information - WiFi signal characteristics containing amplitude and phase data - **DensePose**: Dense human pose estimation mapping 2D detections to 3D body models - **MIMO**: Multiple-Input Multiple-Output antenna configuration - **AP@50**: Average Precision at 50% Intersection over Union - **FPS**: Frames Per Second - **RTMP**: Real-Time Messaging Protocol --- ## 2. Overall Description ### 2.1 Product Perspective The WiFi-DensePose system operates as a standalone platform that integrates with existing WiFi infrastructure to provide human sensing capabilities across multiple domains including healthcare, retail, and security applications. ### 2.2 Product Functions - Real-time human pose estimation through WiFi signals - Multi-person tracking and identification - Cross-wall detection capabilities - Domain-specific analytics and monitoring - Live streaming and visualization - API-based integration with external systems ### 2.3 User Classes - **Healthcare Providers**: Elderly care monitoring, patient activity tracking - **Retail Operators**: Customer analytics, occupancy monitoring - **Security Personnel**: Intrusion detection, perimeter monitoring - **Developers**: API integration, custom application development - **System Administrators**: Deployment, configuration, maintenance --- ## 3. Hardware Requirements ### 3.1 WiFi Router Requirements #### 3.1.1 Compatible Hardware - **Primary**: Atheros-based routers (TP-Link Archer series, Netgear Nighthawk) - **Secondary**: Intel 5300 NIC-based systems - **Alternative**: ASUS RT-AC68U series #### 3.1.2 Antenna Configuration - **Minimum**: 3×3 MIMO antenna configuration - **Spatial Diversity**: Required for CSI spatial measurements - **Frequency Bands**: 2.4GHz and 5GHz support #### 3.1.3 Firmware Requirements - **Base**: OpenWRT firmware compatibility - **Patches**: CSI extraction patches installed - **Monitor Mode**: Capability for monitor mode operation - **Data Streaming**: UDP data stream support #### 3.1.4 Cost Constraints - **Target Cost**: ~$30 per router unit - **Total System**: Under $100 including processing hardware - **Scalability**: 10-100x cost reduction vs. LiDAR alternatives ### 3.2 Processing Hardware Requirements #### 3.2.1 Minimum Specifications - **CPU**: Multi-core processor (4+ cores recommended) - **RAM**: 8GB minimum, 16GB recommended - **Storage**: 50GB available space - **Network**: Gigabit Ethernet for CSI data streams #### 3.2.2 GPU Acceleration (Optional) - **CUDA Support**: NVIDIA GPU with CUDA capability - **Memory**: 4GB+ GPU memory for real-time processing - **Performance**: Sub-100ms processing latency target #### 3.2.3 Network Infrastructure - **Bandwidth**: Minimum 100Mbps for CSI data collection - **Latency**: Low-latency network for real-time processing - **Reliability**: Stable connection for continuous operation --- ## 4. Software Requirements ### 4.1 Operating System Support - **Primary**: Linux (Ubuntu 20.04+, CentOS 8+) - **Secondary**: Windows 10/11 with WSL2 - **Container**: Docker support for deployment ### 4.2 Runtime Dependencies - **Python**: 3.8+ with pip package management - **PyTorch**: GPU-accelerated deep learning framework - **OpenCV**: Computer vision and image processing - **FFmpeg**: Video encoding for streaming - **FastAPI**: Web framework for API services ### 4.3 Development Dependencies - **Testing**: pytest, unittest framework - **Documentation**: Sphinx, markdown support - **Linting**: flake8, black code formatting - **Version Control**: Git integration --- ## 5. Performance Requirements ### 5.1 Accuracy Metrics - **Primary Target**: 87.2% AP@50 under optimal conditions - **Cross-Environment**: 51.8% AP@50 minimum performance - **Multi-Person**: Support for up to 5 individuals simultaneously - **Tracking Consistency**: Minimal ID switching during occlusion ### 5.2 Real-Time Performance - **Processing Rate**: 10-30 FPS depending on hardware - **End-to-End Latency**: Under 100ms on GPU systems - **Startup Time**: System ready within 30 seconds - **Memory Usage**: Stable operation without memory leaks ### 5.3 Reliability Requirements - **Uptime**: 99.5% availability for continuous operation - **Error Recovery**: Automatic recovery from transient failures - **Data Integrity**: No data loss during normal operation - **Graceful Degradation**: Reduced performance under resource constraints ### 5.4 Scalability Requirements - **Concurrent Users**: Support 100+ API clients - **Data Throughput**: Handle continuous CSI streams - **Storage Growth**: Efficient data management for historical data - **Horizontal Scaling**: Support for distributed deployments --- ## 6. Security Requirements ### 6.1 Privacy Protection - **No Visual Data**: Complete elimination of camera-based sensing - **Anonymous Tracking**: Pose data without identity information - **Data Encryption**: Encrypted data transmission and storage - **Access Control**: Role-based access to system functions ### 6.2 Network Security - **Secure Communication**: HTTPS/WSS for all external interfaces - **Authentication**: API key-based authentication - **Input Validation**: Comprehensive input sanitization - **Rate Limiting**: Protection against abuse and DoS attacks ### 6.3 Data Protection - **Local Processing**: On-premises data processing capability - **Data Retention**: Configurable data retention policies - **Audit Logging**: Comprehensive system activity logging - **Compliance**: GDPR and healthcare privacy compliance --- ## 7. Environmental Requirements ### 7.1 Physical Environment - **Operating Temperature**: 0°C to 40°C - **Humidity**: 10% to 90% non-condensing - **Ventilation**: Adequate cooling for processing hardware - **Power**: Stable power supply with UPS backup recommended ### 7.2 RF Environment - **Interference**: Tolerance to common WiFi interference - **Range**: Effective operation within 10-30 meter range - **Obstacles**: Through-wall detection capability - **Multi-Path**: Robust operation in complex RF environments ### 7.3 Installation Requirements - **Router Placement**: Strategic positioning for coverage - **Network Configuration**: Isolated or VLAN-based deployment - **Calibration**: Environmental baseline establishment - **Maintenance Access**: Physical and remote access for updates --- ## 8. Compliance and Standards ### 8.1 Regulatory Compliance - **FCC Part 15**: WiFi equipment certification - **IEEE 802.11**: WiFi standard compliance - **IEEE 802.11bf**: Future WiFi sensing standard compatibility - **Local Regulations**: Regional RF emission compliance ### 8.2 Industry Standards - **ISO 27001**: Information security management - **HIPAA**: Healthcare data protection (where applicable) - **GDPR**: European data protection regulation - **SOC 2**: Service organization control standards --- ## 9. Quality Attributes ### 9.1 Usability - **Installation**: Automated setup and configuration - **Interface**: Intuitive web-based dashboard - **Documentation**: Comprehensive user and API documentation - **Support**: Multi-language support for international deployment ### 9.2 Maintainability - **Modular Design**: Component-based architecture - **Logging**: Comprehensive system and error logging - **Monitoring**: Real-time system health monitoring - **Updates**: Rolling updates without service interruption ### 9.3 Portability - **Cross-Platform**: Support for multiple operating systems - **Containerization**: Docker-based deployment - **Cloud Compatibility**: Support for cloud deployment - **Hardware Independence**: Adaptation to different hardware configurations --- ## 10. Constraints and Assumptions ### 10.1 Technical Constraints - **WiFi Dependency**: Requires compatible WiFi hardware - **Processing Power**: Performance scales with available compute resources - **Network Bandwidth**: CSI data requires significant bandwidth - **Environmental Factors**: Performance affected by RF environment ### 10.2 Business Constraints - **Cost Targets**: Maintain affordability for widespread adoption - **Time to Market**: Rapid deployment capability - **Regulatory Approval**: Compliance with local regulations - **Intellectual Property**: Respect for existing patents and IP ### 10.3 Assumptions - **Network Stability**: Reliable network infrastructure - **Power Availability**: Stable power supply - **User Training**: Basic technical competency for deployment - **Maintenance**: Regular system maintenance and updates --- ## 11. Acceptance Criteria ### 11.1 Functional Acceptance - **Pose Detection**: Successful human pose estimation - **Multi-Person**: Concurrent tracking of multiple individuals - **Real-Time**: Sub-100ms latency performance - **API Functionality**: All specified endpoints operational ### 11.2 Performance Acceptance - **Accuracy**: Meet specified AP@50 targets - **Throughput**: Achieve target FPS rates - **Reliability**: 99.5% uptime over 30-day period - **Resource Usage**: Operate within specified hardware limits ### 11.3 Integration Acceptance - **External APIs**: Successful integration with specified services - **Streaming**: Functional Restream integration - **Webhooks**: Reliable event notification delivery - **MQTT**: Successful IoT ecosystem integration // TEST: Verify all hardware requirements are met during system setup // TEST: Validate performance metrics under various load conditions // TEST: Confirm security requirements through penetration testing // TEST: Verify compliance with regulatory standards // TEST: Validate acceptance criteria through comprehensive testing