International Journal of Advanced Research in Computer and Communication Engineering

Abstract: Rapid identification of emergency vehicles is crucial for enabling timely intervention and reducing the risk of accidents in urban traffic environments. Accidents are inevitable in our daily life. To minimize the occurrence of accidents, implementing efficient and well-managed traffic systems is essential. A surveillance system called smart detection of emergency vehicles can identify emergency vehicles that are stuck in traffic. This system supports smarter traffic management in response to the growing number of vehicles on the road in recent years, which has led to increasing congestion. In this paper, we present a prototype of a traffic control system designed to manage signal lights at a junction. When an emergency vehicle approaches, the system temporarily overrides the normal signal cycle and prioritizes its movement by indicating its entry. This ensures that the emergency vehicle can pass through the junction in the shortest possible time. When an emergency vehicle enters, the system will stop the present status of work temporarily and will indicate the entry of the emergency vehicle. So that it can pass through the junctions in a lowest possible time. To achieve this we have utilised a Camera module which helps in identifying or capturing the real time images in the traffic, this camera module is paired with Raspberry Pi 4 as the main controller, the software is implemented in Python, utilising the YOLO framework, and the final implementation is done through a led module which helps in regulating the traffic signals. Since it the proto type the desired implementation is done for only one of the line of the traffic junction.
Keywords: Machine Learning, Image Processing, Segmentation, Early Detection, Artificial Intelligence.

Downloads: | DOI: 10.17148/IJARCCE.2025.141203