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qt_app_pyside1/docs/user-guide/how-to-use-smart-intersection.md
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qt_app_pyside1/docs/user-guide/how-to-use-smart-intersection.md
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# How to Use Smart Intersection Features in Desktop App
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This guide explains how to use the Smart Intersection analytics features integrated into the Traffic Monitoring Desktop Application.
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## Overview
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The Smart Intersection features provide advanced scene-based analytics for traffic monitoring, including multi-camera object tracking and region-of-interest analysis.
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## Getting Started
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### 1. Launch the Application
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- Run `python main.py` from the qt_app_pyside1 directory
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- The application will start with Intel Arc GPU acceleration enabled
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- Wait for the splash screen to complete initialization
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### 2. Access Smart Intersection Features
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#### Configuration Panel
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1. Navigate to the **Config** tab in the main window
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2. Select **Smart Intersection** from the configuration categories
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3. Configure the following settings:
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- **Camera Settings**: Add multiple camera sources for scene analytics
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- **Tracker Parameters**: Adjust tracking sensitivity and frame rate handling
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- **ROI Definition**: Define regions of interest for analytics
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- **Performance Settings**: Optimize for your Intel Arc GPU
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#### Analytics Dashboard
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1. Go to the **Analytics** tab
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2. View real-time scene analytics including:
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- Multi-camera object tracking
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- Region-based event detection
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- Traffic flow analysis
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- Pedestrian safety monitoring
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#### VLM Insights
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1. The VLM insights panel provides AI-powered analysis
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2. Enable scene-based insights for enhanced understanding
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3. View contextual information about detected events
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## Key Features
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### Multi-Camera Scene Analytics
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- **Object Tracking**: Track objects across multiple camera views
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- **Scene Fusion**: Combine data from multiple cameras for comprehensive view
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- **Real-time Processing**: All processing occurs locally with GPU acceleration
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### Region of Interest (ROI) Analytics
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- **Crosswalk Monitoring**: Detect pedestrians in crosswalk areas
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- **Lane Analysis**: Monitor vehicle dwell time and traffic flow
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- **Safety Zones**: Define areas for safety monitoring and alerts
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### Performance Optimization
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- **Intel Arc GPU**: Optimized for Intel Arc GPU acceleration
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- **Local Processing**: No cloud dependency, all processing local
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- **Real-time Feedback**: Immediate response to traffic events
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## Configuration Options
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### Tracker Settings
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```json
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{
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"max_unreliable_frames": 10,
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"non_measurement_frames_dynamic": 8,
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"non_measurement_frames_static": 16,
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"baseline_frame_rate": 30
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}
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```
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### Camera Configuration
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- **Camera ID**: Unique identifier for each camera
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- **Position**: Physical position in the intersection
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- **Calibration**: Camera calibration parameters
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- **ROI Mapping**: Define which regions each camera monitors
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## Troubleshooting
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### Common Issues
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1. **GPU Not Detected**: Ensure Intel Arc GPU drivers are installed
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2. **Poor Tracking**: Adjust tracker parameters in configuration
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3. **Performance Issues**: Check GPU utilization in Performance tab
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### Performance Tips
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- Use appropriate frame rates for your hardware
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- Configure ROI regions efficiently
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- Monitor GPU memory usage
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- Adjust tracking parameters based on scene complexity
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## Advanced Usage
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### Custom ROI Definition
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1. Load video or connect cameras
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2. Pause on a representative frame
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3. Use the ROI drawing tools to define areas
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4. Save configuration for reuse
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### Integration with Existing Workflows
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- Export analytics data for further analysis
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- Configure alerts for specific events
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- Integrate with external systems via configuration
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## Support
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For additional help:
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- Check the **Help** → **User Guide** menu
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- Review system requirements
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- Consult troubleshooting documentation
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- Check performance metrics in the Performance tab
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# Smart Intersection Analytics - Desktop Integration
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## Overview
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This documentation describes the Smart Intersection analytics capabilities integrated into the Traffic Monitoring Desktop Application. The system demonstrates how edge AI technologies can address traffic management challenges using scene-based analytics.
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## Key Features Integrated
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### Multi-Camera Scene Analytics
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- **Multi-camera multi-object tracking**: Enables tracking of objects across multiple camera views
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- **Scene based analytics**: Regions of interest that span multiple views can be easily defined
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- **Real-time processing**: Object tracks and analytics available in near real-time
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### Use Cases
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- **Pedestrian Safety**: Enhance safety for vulnerable road users (VRUs) at crosswalks
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- Scene-based region of interest (ROI) analytics help identify VRUs actively using crosswalks
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- Detect unsafe situations, such as pedestrians walking outside designated crosswalk areas
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- **Vehicle Analytics**: Measure average vehicle count and average dwell time in each lane
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- Vehicles spending too much time in a lane indicates anomalies such as stalled vehicles, accidents, and congestion
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### Desktop Application Benefits
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- **Reduced TCO**: Works with existing cameras and simplifies business logic development
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- **Local Processing**: All analytics run locally with Intel Arc GPU acceleration
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- **Integrated UI**: Scene analytics configuration and monitoring within the main application
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- **Real-time Insights**: VLM-powered insights for enhanced understanding of traffic patterns
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## Configuration
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### Scene Analytics Settings
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The application includes configuration options for:
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- **Tracker Parameters**: Frame rate handling, measurement thresholds
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- **Camera Setup**: Multi-camera calibration and positioning
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- **ROI Definition**: Define regions of interest for analytics
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- **Performance Tuning**: Optimize for Intel Arc GPU acceleration
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### Access Through UI
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- Navigate to the **Config** tab in the main application
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- Select **Smart Intersection** settings
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- Configure parameters and apply changes
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- View live analytics in the **Analytics** tab
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## Technical Integration
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The desktop application integrates scene-based analytics through:
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- **Scene Adapter**: Python utilities for object detection processing
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- **Configuration Management**: JSON-based settings for tracker and scene parameters
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- **Signal Processing**: Qt signals for real-time data flow between components
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- **GPU Acceleration**: OpenVINO optimized pipelines for Intel Arc GPU
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## Getting Started
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1. Open the Traffic Monitoring Desktop Application
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2. Navigate to **Config** → **Smart Intersection**
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3. Configure your camera settings and ROI definitions
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4. Apply settings and view analytics in the **Analytics** tab
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5. Access detailed insights through the **Help** → **User Guide** menu
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