Emergency Vehicle Detection Using Deep Learning Algorithm

The main purpose of the project is to find a solution for traffic congestion which may hinder the movement of emergency vehicles such as ambulances, fire engines, and police cars. A proposed deep learning-based emergency vehicle detection system using Convolutional Neural Networks(CNNs) with You Only Look Once (YOLO) is devised that detects primary emergency vehicles and classifies classes from external images. After detection, the system pushes notifications to the nearest traffic signal interface to allow for timely clearance for emergency vehicles and smooth clearance of the paths. A user-friendly web application based on Streamlit for visualization detection including alert monitoring has been developed. An approach such as this will improve emergency response time all while managing a systematic traffic flow in smart city infrastructure.