I got the idea for this project by observing how ambulances and other emergency vehicles often get stuck in traffic at signals. I thought that if traffic signals could automatically detect emergency vehicles and give them priority, it could help save valuable time and possibly save lives.
What it does
My project detects emergency vehicles such as ambulances, fire trucks, and police vehicles using AI through existing roadside or street cameras and automatically gives them priority at traffic signals so they can pass through intersections quickly.
How we built it
In this project I used Python, OpenCV, and an AI object detection model to analyze video input from traffic cameras and identify emergency vehicles. When an emergency vehicle is detected, the system triggers a smart traffic signal control mechanism to give that route a green signal.
Challenges we ran into
One of the main challenges in this project was detecting emergency vehicles accurately in different traffic conditions, lighting situations, and crowded roads.
Accomplishments that we're proud of
I am proud that my project shows how existing surveillance cameras and AI technology can be combined to improve traffic management and help emergency vehicles move faster.
What we learned
Through this project I learned about AI-based vehicle detection, computer vision techniques, and how intelligent traffic systems can be designed to support smart city infrastructure.
What's next for AI-Based Emergency Vehicle Detection and Smart Traffic Control
In the future I plan to improve the detection accuracy, integrate the system with real traffic signal networks, and expand it so that it can work across multiple intersections in a smart city environment. 🚦
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