Traffic-Intersection-Monitoring/qt_app_pyside1/docs/user-guide/smart-intersection-overview.md

Smart Intersection Analytics - Desktop Integration

Overview

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.

Key Features Integrated

Multi-Camera Scene Analytics

• Multi-camera multi-object tracking: Enables tracking of objects across multiple camera views
• Scene based analytics: Regions of interest that span multiple views can be easily defined
• Real-time processing: Object tracks and analytics available in near real-time

Use Cases

• Pedestrian Safety: Enhance safety for vulnerable road users (VRUs) at crosswalks
  • Scene-based region of interest (ROI) analytics help identify VRUs actively using crosswalks
  • Detect unsafe situations, such as pedestrians walking outside designated crosswalk areas
• Vehicle Analytics: Measure average vehicle count and average dwell time in each lane
  • Vehicles spending too much time in a lane indicates anomalies such as stalled vehicles, accidents, and congestion

Desktop Application Benefits

• Reduced TCO: Works with existing cameras and simplifies business logic development
• Local Processing: All analytics run locally with Intel Arc GPU acceleration
• Integrated UI: Scene analytics configuration and monitoring within the main application
• Real-time Insights: VLM-powered insights for enhanced understanding of traffic patterns

Configuration

Scene Analytics Settings

The application includes configuration options for:

• Tracker Parameters: Frame rate handling, measurement thresholds
• Camera Setup: Multi-camera calibration and positioning
• ROI Definition: Define regions of interest for analytics
• Performance Tuning: Optimize for Intel Arc GPU acceleration

Access Through UI

• Navigate to the Config tab in the main application
• Select Smart Intersection settings
• Configure parameters and apply changes
• View live analytics in the Analytics tab

Technical Integration

The desktop application integrates scene-based analytics through:

• Scene Adapter: Python utilities for object detection processing
• Configuration Management: JSON-based settings for tracker and scene parameters
• Signal Processing: Qt signals for real-time data flow between components
• GPU Acceleration: OpenVINO optimized pipelines for Intel Arc GPU

Getting Started

1. Open the Traffic Monitoring Desktop Application
2. Navigate to Config → Smart Intersection
3. Configure your camera settings and ROI definitions
4. Apply settings and view analytics in the Analytics tab
5. Access detailed insights through the Help → User Guide menu