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This project aims to optimize traffic flow using machine learning algorithms to intelligently manage green signal timings based on real-time traffic data. By analyzing the number of vehicles passing through intersections, the system dynamically adjusts signal durations to reduce congestion and enhance overall traffic efficiency.

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PIYUSH-JOSHI1/UST

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Track-V: Advanced Traffic Management Dashboard

Overview

Track-V is a comprehensive traffic management dashboard designed for law enforcement and city planners. It provides real-time monitoring of traffic conditions, weather impacts, and inspector management across multiple junctions in a city.

Features

  • Real-time Traffic Monitoring: View live video feeds and traffic statistics from multiple junctions.
  • Interactive Dashboard: Responsive design with dark/light mode toggle.
  • Detailed Reports: Analyze traffic predictions, density, and congestion levels with interactive charts.
  • Weather Integration: Monitor current weather conditions and their impact on traffic flow.
  • Inspector Management: Add, remove, and manage traffic inspectors for each junction.
  • Map View: Visualize junction locations and access video feeds directly from the map.
  • Alert System: Send instant alerts to nearby junctions in case of emergencies.
  • Officer Profiles: View and manage individual officer performance and activities.
  • System Mode Switch: Toggle between automatic and manual traffic management modes.

Technologies Used

  • HTML5
  • CSS3 (with custom properties for theming)
  • JavaScript (ES6+)
  • Chart.js for data visualization
  • No external CSS frameworks - custom styling throughout

Setup and Installation

  1. Clone the repository:
https://github.com/PIYUSH-JOSHI1/UST.git

  1. Navigate to the project directory:
cd track-v
  1. Open the index.html file in a modern web browser.

Note: This project is currently a front-end only implementation. For a full-scale deployment, you would need to set up a back-end server and database.

Usage

  • Use the sidebar to navigate between different sections of the dashboard.
  • In the main dashboard, you can view real-time traffic data and send alerts.
  • The Reports section provides detailed analytics and predictions.
  • Manage inspector assignments in the Inspectors section.
  • Toggle between dark and light modes in the Settings section.
  • View weather data and its impact on traffic in the Weather section.
  • Use the Map View to get a geographical overview of all junctions.

Customization

  • To add new junctions or modify existing ones, update the relevant sections in the HTML and JavaScript code.
  • Customize the charts in the createPredictionChart, createDensityChart, and createCongestionChart functions.
  • Modify the updateWeatherInfo function to integrate with a real weather API.

Future Enhancements

  • Backend integration for real-time data processing and storage.
  • User authentication and role-based access control.
  • Mobile app version for on-the-go monitoring.
  • Integration with traffic light control systems for automated management.
  • Machine learning models for more accurate traffic predictions.

Contributing

Contributions to Track-V are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

Contact

For any queries or suggestions, please open an issue in the GitHub repository.


Developed with ❤️ by Trac-v Team

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This project aims to optimize traffic flow using machine learning algorithms to intelligently manage green signal timings based on real-time traffic data. By analyzing the number of vehicles passing through intersections, the system dynamically adjusts signal durations to reduce congestion and enhance overall traffic efficiency.

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