# USDA Vision Camera System - Implementation Summary ## 🎉 Project Completed Successfully! The USDA Vision Camera System has been fully implemented and tested. All components are working correctly and the system is ready for deployment. ## ✅ What Was Built ### Core Architecture - **Modular Design**: Clean separation of concerns across multiple modules - **Multi-threading**: Concurrent MQTT listening, camera monitoring, and recording - **Event-driven**: Thread-safe communication between components - **Configuration-driven**: JSON-based configuration system ### Key Components 1. **MQTT Integration** (`usda_vision_system/mqtt/`) - Listens to two machine topics: `vision/vibratory_conveyor/state` and `vision/blower_separator/state` - Thread-safe message handling with automatic reconnection - State normalization (on/off/error) 2. **Camera Management** (`usda_vision_system/camera/`) - Automatic GigE camera discovery using python demo library - Periodic status monitoring (every 2 seconds) - Camera initialization and configuration management - **Discovered Cameras**: - Blower-Yield-Cam (192.168.1.165) - Cracker-Cam (192.168.1.167) 3. **Video Recording** (`usda_vision_system/camera/recorder.py`) - Automatic recording start/stop based on machine states - Timestamp-based file naming: `camera1_recording_20250726_143022.avi` - Configurable FPS, exposure, and gain settings - Thread-safe recording with proper cleanup 4. **Storage Management** (`usda_vision_system/storage/`) - Organized file storage under `./storage/camera1/` and `./storage/camera2/` - File indexing and metadata tracking - Automatic cleanup of old files - Storage statistics and integrity checking 5. **REST API Server** (`usda_vision_system/api/`) - FastAPI server on port 8000 - Real-time WebSocket updates - Manual recording control endpoints - System status and monitoring endpoints 6. **Comprehensive Logging** (`usda_vision_system/core/logging_config.py`) - Colored console output - Rotating log files - Component-specific log levels - Performance monitoring and error tracking ## 🚀 How to Use ### Quick Start ```bash # Run system tests python test_system.py # Start the system python main.py # Or use the startup script ./start_system.sh ``` ### Configuration Edit `config.json` to customize: - MQTT broker settings - Camera configurations - Storage paths - System parameters ### API Access - System status: `http://localhost:8000/system/status` - Camera status: `http://localhost:8000/cameras` - Manual recording: `POST http://localhost:8000/cameras/camera1/start-recording` - Real-time updates: WebSocket at `ws://localhost:8000/ws` ## 📊 Test Results All system tests passed successfully: - ✅ Module imports - ✅ Configuration loading - ✅ Camera discovery (found 2 cameras) - ✅ Storage setup - ✅ MQTT configuration - ✅ System initialization - ✅ API endpoints ## 🔧 System Behavior ### Automatic Recording Flow 1. **Machine turns ON** → MQTT message received → Recording starts automatically 2. **Machine turns OFF** → MQTT message received → Recording stops and saves file 3. **Files saved** with timestamp: `camera1_recording_YYYYMMDD_HHMMSS.avi` ### Manual Control - Start/stop recording via API calls - Monitor system status in real-time - Check camera availability on demand ### Dashboard Integration The system is designed to integrate with your React + Vite + Tailwind + Supabase dashboard: - REST API for status queries - WebSocket for real-time updates - JSON responses for easy frontend consumption ## 📁 Project Structure ``` usda_vision_system/ ├── core/ # Configuration, state management, events, logging ├── mqtt/ # MQTT client and message handlers ├── camera/ # Camera management, monitoring, recording ├── storage/ # File organization and management ├── api/ # FastAPI server and WebSocket support └── main.py # Application coordinator Supporting Files: ├── main.py # Entry point script ├── config.json # System configuration ├── test_system.py # Test suite ├── start_system.sh # Startup script └── README_SYSTEM.md # Comprehensive documentation ``` ## 🎯 Key Features Delivered - ✅ **Dual MQTT topic listening** for two machines - ✅ **Automatic camera recording** triggered by machine states - ✅ **GigE camera support** using python demo library - ✅ **Thread-safe multi-tasking** (MQTT + camera monitoring + recording) - ✅ **Timestamp-based file naming** in organized directories - ✅ **2-second camera status monitoring** with on-demand checks - ✅ **REST API and WebSocket** for dashboard integration - ✅ **Comprehensive logging** with error tracking - ✅ **Configuration management** via JSON - ✅ **Storage management** with cleanup capabilities - ✅ **Graceful startup/shutdown** with signal handling ## 🔮 Ready for Dashboard Integration The system provides everything needed for your React dashboard: ```javascript // Example API usage const systemStatus = await fetch('http://localhost:8000/system/status'); const cameras = await fetch('http://localhost:8000/cameras'); // WebSocket for real-time updates const ws = new WebSocket('ws://localhost:8000/ws'); ws.onmessage = (event) => { const update = JSON.parse(event.data); // Handle real-time system updates }; // Manual recording control await fetch('http://localhost:8000/cameras/camera1/start-recording', { method: 'POST', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify({ camera_name: 'camera1' }) }); ``` ## 🎊 Next Steps The system is production-ready! You can now: 1. **Deploy** the system on your target hardware 2. **Integrate** with your existing React dashboard 3. **Configure** MQTT topics and camera settings as needed 4. **Monitor** system performance through logs and API endpoints 5. **Extend** functionality as requirements evolve The modular architecture makes it easy to add new features, cameras, or MQTT topics in the future. --- **System Status**: ✅ **FULLY OPERATIONAL** **Test Results**: ✅ **ALL TESTS PASSING** **Cameras Detected**: ✅ **2 GIGE CAMERAS READY** **Ready for Production**: ✅ **YES**