f3c77b1750
- Implemented the WiFi DensePose model in PyTorch, including CSI phase processing, modality translation, and DensePose prediction heads. - Added a comprehensive training utility for the model, including loss functions and training steps. - Created a CSV file to document hardware specifications, architecture details, training parameters, performance metrics, and advantages of the model.
275 lines
10 KiB
Markdown
275 lines
10 KiB
Markdown
# System Requirements Specification (SRS)
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## WiFi-DensePose System
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### Document Information
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- **Version**: 1.0
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- **Date**: 2025-01-07
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- **Project**: InvisPose - WiFi-Based Dense Human Pose Estimation
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- **Status**: Draft
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---
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## 1. Introduction
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### 1.1 Purpose
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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.
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### 1.2 Scope
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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.
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### 1.3 Definitions and Acronyms
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- **CSI**: Channel State Information - WiFi signal characteristics containing amplitude and phase data
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- **DensePose**: Dense human pose estimation mapping 2D detections to 3D body models
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- **MIMO**: Multiple-Input Multiple-Output antenna configuration
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- **AP@50**: Average Precision at 50% Intersection over Union
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- **FPS**: Frames Per Second
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- **RTMP**: Real-Time Messaging Protocol
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---
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## 2. Overall Description
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### 2.1 Product Perspective
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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.
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### 2.2 Product Functions
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- Real-time human pose estimation through WiFi signals
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- Multi-person tracking and identification
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- Cross-wall detection capabilities
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- Domain-specific analytics and monitoring
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- Live streaming and visualization
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- API-based integration with external systems
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### 2.3 User Classes
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- **Healthcare Providers**: Elderly care monitoring, patient activity tracking
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- **Retail Operators**: Customer analytics, occupancy monitoring
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- **Security Personnel**: Intrusion detection, perimeter monitoring
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- **Developers**: API integration, custom application development
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- **System Administrators**: Deployment, configuration, maintenance
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---
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## 3. Hardware Requirements
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### 3.1 WiFi Router Requirements
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#### 3.1.1 Compatible Hardware
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- **Primary**: Atheros-based routers (TP-Link Archer series, Netgear Nighthawk)
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- **Secondary**: Intel 5300 NIC-based systems
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- **Alternative**: ASUS RT-AC68U series
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#### 3.1.2 Antenna Configuration
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- **Minimum**: 3×3 MIMO antenna configuration
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- **Spatial Diversity**: Required for CSI spatial measurements
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- **Frequency Bands**: 2.4GHz and 5GHz support
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#### 3.1.3 Firmware Requirements
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- **Base**: OpenWRT firmware compatibility
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- **Patches**: CSI extraction patches installed
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- **Monitor Mode**: Capability for monitor mode operation
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- **Data Streaming**: UDP data stream support
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#### 3.1.4 Cost Constraints
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- **Target Cost**: ~$30 per router unit
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- **Total System**: Under $100 including processing hardware
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- **Scalability**: 10-100x cost reduction vs. LiDAR alternatives
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### 3.2 Processing Hardware Requirements
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#### 3.2.1 Minimum Specifications
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- **CPU**: Multi-core processor (4+ cores recommended)
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- **RAM**: 8GB minimum, 16GB recommended
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- **Storage**: 50GB available space
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- **Network**: Gigabit Ethernet for CSI data streams
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#### 3.2.2 GPU Acceleration (Optional)
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- **CUDA Support**: NVIDIA GPU with CUDA capability
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- **Memory**: 4GB+ GPU memory for real-time processing
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- **Performance**: Sub-100ms processing latency target
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#### 3.2.3 Network Infrastructure
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- **Bandwidth**: Minimum 100Mbps for CSI data collection
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- **Latency**: Low-latency network for real-time processing
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- **Reliability**: Stable connection for continuous operation
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---
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## 4. Software Requirements
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### 4.1 Operating System Support
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- **Primary**: Linux (Ubuntu 20.04+, CentOS 8+)
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- **Secondary**: Windows 10/11 with WSL2
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- **Container**: Docker support for deployment
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### 4.2 Runtime Dependencies
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- **Python**: 3.8+ with pip package management
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- **PyTorch**: GPU-accelerated deep learning framework
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- **OpenCV**: Computer vision and image processing
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- **FFmpeg**: Video encoding for streaming
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- **FastAPI**: Web framework for API services
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### 4.3 Development Dependencies
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- **Testing**: pytest, unittest framework
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- **Documentation**: Sphinx, markdown support
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- **Linting**: flake8, black code formatting
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- **Version Control**: Git integration
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---
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## 5. Performance Requirements
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### 5.1 Accuracy Metrics
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- **Primary Target**: 87.2% AP@50 under optimal conditions
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- **Cross-Environment**: 51.8% AP@50 minimum performance
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- **Multi-Person**: Support for up to 5 individuals simultaneously
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- **Tracking Consistency**: Minimal ID switching during occlusion
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### 5.2 Real-Time Performance
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- **Processing Rate**: 10-30 FPS depending on hardware
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- **End-to-End Latency**: Under 100ms on GPU systems
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- **Startup Time**: System ready within 30 seconds
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- **Memory Usage**: Stable operation without memory leaks
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### 5.3 Reliability Requirements
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- **Uptime**: 99.5% availability for continuous operation
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- **Error Recovery**: Automatic recovery from transient failures
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- **Data Integrity**: No data loss during normal operation
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- **Graceful Degradation**: Reduced performance under resource constraints
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### 5.4 Scalability Requirements
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- **Concurrent Users**: Support 100+ API clients
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- **Data Throughput**: Handle continuous CSI streams
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- **Storage Growth**: Efficient data management for historical data
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- **Horizontal Scaling**: Support for distributed deployments
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---
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## 6. Security Requirements
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### 6.1 Privacy Protection
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- **No Visual Data**: Complete elimination of camera-based sensing
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- **Anonymous Tracking**: Pose data without identity information
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- **Data Encryption**: Encrypted data transmission and storage
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- **Access Control**: Role-based access to system functions
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### 6.2 Network Security
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- **Secure Communication**: HTTPS/WSS for all external interfaces
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- **Authentication**: API key-based authentication
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- **Input Validation**: Comprehensive input sanitization
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- **Rate Limiting**: Protection against abuse and DoS attacks
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### 6.3 Data Protection
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- **Local Processing**: On-premises data processing capability
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- **Data Retention**: Configurable data retention policies
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- **Audit Logging**: Comprehensive system activity logging
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- **Compliance**: GDPR and healthcare privacy compliance
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---
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## 7. Environmental Requirements
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### 7.1 Physical Environment
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- **Operating Temperature**: 0°C to 40°C
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- **Humidity**: 10% to 90% non-condensing
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- **Ventilation**: Adequate cooling for processing hardware
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- **Power**: Stable power supply with UPS backup recommended
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### 7.2 RF Environment
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- **Interference**: Tolerance to common WiFi interference
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- **Range**: Effective operation within 10-30 meter range
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- **Obstacles**: Through-wall detection capability
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- **Multi-Path**: Robust operation in complex RF environments
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### 7.3 Installation Requirements
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- **Router Placement**: Strategic positioning for coverage
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- **Network Configuration**: Isolated or VLAN-based deployment
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- **Calibration**: Environmental baseline establishment
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- **Maintenance Access**: Physical and remote access for updates
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---
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## 8. Compliance and Standards
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### 8.1 Regulatory Compliance
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- **FCC Part 15**: WiFi equipment certification
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- **IEEE 802.11**: WiFi standard compliance
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- **IEEE 802.11bf**: Future WiFi sensing standard compatibility
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- **Local Regulations**: Regional RF emission compliance
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### 8.2 Industry Standards
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- **ISO 27001**: Information security management
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- **HIPAA**: Healthcare data protection (where applicable)
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- **GDPR**: European data protection regulation
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- **SOC 2**: Service organization control standards
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---
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## 9. Quality Attributes
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### 9.1 Usability
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- **Installation**: Automated setup and configuration
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- **Interface**: Intuitive web-based dashboard
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- **Documentation**: Comprehensive user and API documentation
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- **Support**: Multi-language support for international deployment
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### 9.2 Maintainability
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- **Modular Design**: Component-based architecture
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- **Logging**: Comprehensive system and error logging
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- **Monitoring**: Real-time system health monitoring
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- **Updates**: Rolling updates without service interruption
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### 9.3 Portability
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- **Cross-Platform**: Support for multiple operating systems
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- **Containerization**: Docker-based deployment
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- **Cloud Compatibility**: Support for cloud deployment
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- **Hardware Independence**: Adaptation to different hardware configurations
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---
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## 10. Constraints and Assumptions
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### 10.1 Technical Constraints
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- **WiFi Dependency**: Requires compatible WiFi hardware
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- **Processing Power**: Performance scales with available compute resources
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- **Network Bandwidth**: CSI data requires significant bandwidth
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- **Environmental Factors**: Performance affected by RF environment
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### 10.2 Business Constraints
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- **Cost Targets**: Maintain affordability for widespread adoption
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- **Time to Market**: Rapid deployment capability
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- **Regulatory Approval**: Compliance with local regulations
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- **Intellectual Property**: Respect for existing patents and IP
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### 10.3 Assumptions
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- **Network Stability**: Reliable network infrastructure
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- **Power Availability**: Stable power supply
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- **User Training**: Basic technical competency for deployment
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- **Maintenance**: Regular system maintenance and updates
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---
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## 11. Acceptance Criteria
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### 11.1 Functional Acceptance
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- **Pose Detection**: Successful human pose estimation
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- **Multi-Person**: Concurrent tracking of multiple individuals
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- **Real-Time**: Sub-100ms latency performance
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- **API Functionality**: All specified endpoints operational
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### 11.2 Performance Acceptance
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- **Accuracy**: Meet specified AP@50 targets
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- **Throughput**: Achieve target FPS rates
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- **Reliability**: 99.5% uptime over 30-day period
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- **Resource Usage**: Operate within specified hardware limits
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### 11.3 Integration Acceptance
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- **External APIs**: Successful integration with specified services
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- **Streaming**: Functional Restream integration
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- **Webhooks**: Reliable event notification delivery
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- **MQTT**: Successful IoT ecosystem integration
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// TEST: Verify all hardware requirements are met during system setup
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// TEST: Validate performance metrics under various load conditions
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// TEST: Confirm security requirements through penetration testing
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// TEST: Verify compliance with regulatory standards
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// TEST: Validate acceptance criteria through comprehensive testing |