Traffic Clearance System for Emerygency Vehicals

The Smart Traffic Management System with Ambulance Detection is an IoT and computer vision-based solution that prioritizes emergency vehicles. It automatically detects ambulances using OpenCV to process images of red-cross patterns. The system uses a Raspberry Pi 4B to control LED traffic lights, a servo-controlled camera, and emergency indicators. A Flask web dashboard allows for real-time monitoring and control. Key functions include automating three-way traffic lights, rotating the camera in real time, activating a 30-second green light priority mode, providing analytics, and featuring a test mode. The system achieved a 95% detection accuracy in different lighting conditions and reduced response time to under 3 seconds. This improvement supports emergency response while keeping overall traffic efficiency high.

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Publication Details

Journal
International Journal of Advanced Research in Science Communication and Technology
Published
2025-11-09
DOI
https://doi.org/10.48175/ijarsct-29715
Primary Topic
IoT and GPS-based Vehicle Safety Systems
Type
article
Field-Weighted Citation Impact
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article

Traffic Clearance System for Emerygency Vehicals

Ankita Bhosale, P. U. Patil, Bhagyashri Gadekar, Ankita Gunjal
International Journal of Advanced Research in Science Communication and Technology
IoT and GPS-based Vehicle Safety Systems
article

Traffic Clearance System for Emerygency Vehicals

Ankita Bhosale, P. U. Patil, Bhagyashri Gadekar, Ankita Gunjal
article en

Abstract

The Smart Traffic Management System with Ambulance Detection is an IoT and computer vision-based solution that prioritizes emergency vehicles. It automatically detects ambulances using OpenCV to process images of red-cross patterns. The system uses a Raspberry Pi 4B to control LED traffic lights, a servo-controlled camera, and emergency indicators. A Flask web dashboard allows for real-time monitoring and control. Key functions include automating three-way traffic lights, rotating the camera in real time, activating a 30-second green light priority mode, providing analytics, and featuring a test mode. The system achieved a 95% detection accuracy in different lighting conditions and reduced response time to under 3 seconds. This improvement supports emergency response while keeping overall traffic efficiency high.

International Journal of Advanced Research in Science Communication and Technology
Indian Numismatic, Historical and Cultural Research Foundation (IN)
Openalex Percentile: Top 65%
IoT and GPS-based Vehicle Safety Systems
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