1. Rijans Bhagat
2. Setu Parmar
3. Kushagra Saruparia

In modern cities, the bane of daily commute is often unpredictable traffic congestion. With the current infrastructure, traffic light timings are mostly static and don't adapt to real-time traffic conditions. This leads to unnecessary traffic congestion and wastage of time for the daily commuter. Our solution? An intelligent traffic light control system that alters its timings dynamically based on real-time traffic congestion.

• Real-time Traffic Analysis: Using OpenCV, we analyze live camera feeds to assess the volume of traffic in each lane at an intersection.
• Dynamic Traffic Light Timings: Neural network models predict the optimal traffic light durations to minimize congestion.
• Adaptive Learning: Our model becomes more accurate over time as it learns from more data.
• Scalable: Can be easily deployed across multiple intersections and traffic conditions.
• Eco-Friendly: Reducing traffic congestion also means reducing the amount of time cars spend idling, leading to reduced carbon emissions.

• Computer Vision: OpenCV
• Machine Learning: Custom Neural Network using Tensorflow
• Backend: Python Flask
• Frontend: React.js (For traffic data visualization)

1. Clone the Repository

   git clone https://github.com/Tromso-AI-Traffic-Solution/repo.git

2. Set Up the Environment

   pip install -r requirements.txt

3. Run the Application

   python main.py

4. Access the frontend dashboard at http:https://localhost:3000 to visualize real-time data.

• Integration with Smart Cities: Collaborate with municipalities to integrate our solution into existing smart city initiatives.
• Prediction of Traffic Patterns: With enough data, predict future traffic patterns to better prepare for congestion.
• Emergency Vehicle Priority: Detect emergency vehicles and alter traffic lights to give them a clear path.

A special thank you to Hack for India 2023 and Silver Oak University for providing the platform to showcase our solution.

• Rijans Bhagat: [email protected]
• Setu Parmar: [email protected]
• Kushagra Saruparia: [email protected]

Feel free to fork, star 🌟, and contribute to this project. Let's work together to make our cities more efficient and congestion-free!

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