plans/phase1-specification/functional-spec.md
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.
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.
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.
Function: Extract Channel State Information from compatible WiFi routers
Acceptance Criteria:
Function: Clean and normalize raw CSI data for neural network input
Processing Pipeline:
Raw CSI → Phase Unwrapping → Temporal Filtering →
Background Subtraction → Noise Reduction → Normalized CSI
Acceptance Criteria:
Function: Establish baseline measurements for background subtraction
Calibration Process:
Function: Convert 1D CSI signals to 2D spatial representations
Network Architecture:
CSI Input (3×3×N) → Amplitude Branch → Feature Fusion →
Phase Branch → Upsampling → Spatial Features (720×1280×3)
Performance Requirements:
Function: Extract dense human pose from spatial features
Output Format:
Function: Track multiple individuals across frame sequences
Tracking Features:
Function: Orchestrate end-to-end processing pipeline
Pipeline Stages:
Function: Maintain real-time performance under varying loads
Optimization Strategies:
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:
User Journey:
// TEST: Verify fall detection accuracy meets 95% threshold // TEST: Confirm activity tracking provides meaningful health insights // TEST: Validate alert delivery within 2-second requirement
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:
User Journey:
// TEST: Verify exercise classification accuracy for rehabilitation movements // TEST: Confirm progress metrics calculation and visualization // TEST: Validate EHR integration functionality
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:
User Journey:
// TEST: Verify anonymous customer tracking maintains privacy // TEST: Confirm zone analytics provide actionable insights // TEST: Validate A/B testing framework for layout optimization
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:
User Journey:
// TEST: Verify queue detection accuracy in various store layouts // TEST: Confirm wait time calculations are precise // TEST: Validate alert system for queue management
As a security officer I want to monitor restricted areas for unauthorized access So that I can respond quickly to security breaches
Acceptance Criteria:
User Journey:
// TEST: Verify through-wall detection capability // TEST: Confirm real-time alert delivery with accurate location // TEST: Validate integration with security management systems
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:
User Journey:
// TEST: Verify person counting accuracy across different environments // TEST: Confirm occupancy dashboard provides real-time updates // TEST: Validate emergency evacuation support functionality
End-to-End Latency: <100ms from CSI data to pose output
Streaming Latency: <50ms for WebSocket delivery
// TEST: Verify end-to-end latency meets <100ms requirement // TEST: Confirm WebSocket streaming latency <50ms // TEST: Validate latency consistency under varying loads
Processing Throughput: 10-30 FPS depending on hardware
Concurrent Streaming: Support 100+ simultaneous clients
// TEST: Verify processing throughput meets FPS requirements // TEST: Confirm system supports 100+ concurrent streaming clients // TEST: Validate bandwidth utilization stays within limits
WebSocket Streaming: Primary real-time protocol
Server-Sent Events (SSE): Alternative streaming protocol
MQTT Streaming: IoT ecosystem integration
// TEST: Verify WebSocket streaming handles reconnections gracefully // TEST: Confirm SSE provides reliable alternative streaming // TEST: Validate MQTT integration with IoT ecosystems
Quality Adaptation: Automatic quality adjustment based on network conditions
Client Capability Detection: Optimize streaming for client capabilities
// TEST: Verify adaptive streaming adjusts to network conditions // TEST: Confirm client capability detection works accurately // TEST: Validate quality adaptation maintains user experience
Supported Platforms: Multi-platform simultaneous streaming
Stream Configuration: Flexible streaming parameters
// TEST: Verify simultaneous streaming to multiple platforms // TEST: Confirm stream quality meets platform requirements // TEST: Validate custom RTMP endpoint functionality
Pose Overlay Generation: Real-time visualization creation
Stream Composition: Video stream assembly
Performance Optimization: Efficient video processing
// TEST: Verify pose overlay generation meets quality standards // TEST: Confirm stream composition handles multiple elements // TEST: Validate performance optimization maintains real-time processing
Connection Management: Robust streaming infrastructure
Analytics and Monitoring: Stream performance tracking
Configuration Management: Dynamic stream control
// TEST: Verify stream management handles connection failures // TEST: Confirm analytics provide meaningful insights // TEST: Validate configuration changes apply without interruption
Function: Detect and alert on fall events for elderly care
Detection Algorithm:
Pose Trajectory Analysis → Velocity Calculation →
Position Change Detection → Confidence Assessment → Alert Decision
Alert Criteria:
Function: Track patient mobility and activity patterns
Monitored Activities:
Function: Generate health insights while protecting patient privacy
Function: Monitor customer movement and behavior patterns
Analytics Outputs:
Function: Monitor store capacity and density
Capacity Features:
Function: Provide insights for store layout improvements
Function: Monitor restricted areas for unauthorized access
Detection Capabilities:
Function: Enhance physical security systems
Function: Support emergency evacuation and response
Endpoints:
GET /pose/latest - Current pose dataGET /pose/history - Historical pose dataGET /pose/stream - Real-time pose streamPOST /pose/query - Custom pose queriesResponse Format:
{
"timestamp": "2025-01-07T04:46:32Z",
"persons": [
{
"id": 1,
"confidence": 0.87,
"keypoints": [...],
"dense_pose": {...},
"bounding_box": {...}
}
],
"metadata": {
"processing_time": 45,
"frame_id": 12345
}
}
Endpoints:
POST /system/start - Start pose estimationPOST /system/stop - Stop pose estimationGET /system/status - System health statusPOST /system/calibrate - Trigger calibrationEndpoints:
GET /config - Current configurationPUT /config - Update configurationGET /config/templates - Available templatesPOST /config/validate - Validate configurationFunction: Provide low-latency pose data streaming
Stream Types:
Function: Manage WebSocket client lifecycle
Function: Integrate with IoT ecosystems
MQTT Topics:
wifi-densepose/pose/person/{id} - Individual pose datawifi-densepose/alerts/{type} - Alert notificationswifi-densepose/status - System statuswifi-densepose/analytics/{domain} - Domain analyticsFunction: Send real-time notifications to external services
Webhook Events:
Function: Live streaming to multiple platforms
Function: Display live pose estimation results
Visualization Features:
Function: Monitor system health and performance
Function: System configuration and control
Function: Mobile-optimized interface for monitoring
Function: Essential controls for mobile users
Function: Store pose estimation results for analysis
Storage Schema:
pose_data:
- timestamp (primary key)
- person_id
- pose_keypoints
- confidence_scores
- metadata
Function: Persist system configuration and settings
Function: Store aggregated analytics and reports
Function: Process historical data for insights
Function: Generate live insights from streaming data
Function: Comprehensive automated test coverage
Function: Test without physical hardware
Function: Continuous system health assessment
Function: Troubleshooting and problem resolution
// 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