International Journal of Scientific Research and Engineering Development

Rapid identification of emergency vehicles in congested urban traffic is a critical requirement for efficient emergency response and smart city infrastructure. Delays in emergency vehicle movement can lead to severe consequences, including loss of life and property. This paper presents an Emergency Vehicle Detection System, a Python-based intelligent framework that employs computer vision, featurebased image matching, and real-time video processing techniques to detect emergency vehicles from traffic video inputs.The proposed system processes uploaded traffic videos through a web-based interface, extracts individual frames, and applies preprocessing techniques such as resizing, grayscale conversion, and frame optimization to enhance feature extraction. The system utilizes the ORB (Oriented FAST and Rotated BRIEF) algorithm for robust feature detection and matching between video frames and predefined reference images of emergency vehicles. Rule-based decision logic, combined with emergency light and siren pattern detection, ensures accurate classification of ambulances, police vehicles, and fire trucks. The detection results are presented through an interactive dashboard displaying vehicle type, detection confidence, and frame-wise recognition statistics. The modular and scalable design of the system enables seamless integration into intelligent traffic management systems, contributing to reduced emergency response time and improved urban mobility.

Hariharan A, Malathy B, Kiran Sankar S, Shiyam Sundar V,"Emergency Vehicle Detection" International Journal of Scientific Research and Engineering Development, V9(2): Page(274-279) Mar-Apr 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.