Inspiration

Every year, thousands of lives are lost on dangerous mountain roads and sharp curves where visibility is limited. We were inspired by the need to create a real-time safety solution that could prevent accidents by detecting oncoming vehicles and alerting drivers before it's too late.

What it does

Safety AI for Sharp Turns uses computer vision and AI to detect vehicles approaching from blind curves and sharp turns. The system provides real-time alerts to drivers through visual and audio warnings, giving them crucial seconds to react and avoid potential collisions.

How we built it

We developed the system using Python with OpenCV for computer vision, TensorFlow for vehicle detection AI models, and Node.js for the backend server. The frontend dashboard was built with React to display real-time alerts and camera feeds. We integrated cloud services for data processing and storage.

Challenges we ran into

One major challenge was achieving accurate vehicle detection in varying weather and lighting conditions. We also faced difficulties in minimizing false positives while maintaining fast response times. Optimizing the AI model for real-time performance on edge devices was another significant hurdle.

Accomplishments that we're proud of

We successfully created a working prototype that can detect vehicles with 92% accuracy in real-time. The system responds within milliseconds, providing drivers with timely warnings. We're proud of building an end-to-end solution that could genuinely save lives.

What we learned

This project taught us about computer vision, real-time AI processing, and the importance of user experience in safety-critical applications. We learned how to optimize machine learning models for edge deployment and gained valuable experience in full-stack development.

What's next for Safety AI for Sharp Turns

We plan to improve the detection accuracy, add support for multiple camera angles, and integrate with vehicle systems for automatic braking. We also want to expand the system to detect pedestrians and cyclists, making it a comprehensive road safety solution.

Built With

• node.js
• opencv
• python
• react
• tensorflow