AcciAlert: Real-Time Traffic Accident Detection and Emergency Notification System
DOI:
https://doi.org/10.15662/IJEETR.2026.0802246Keywords:
Accident Detection, Deep Learning, Computer Vision, SSD MobileNet, Traffic Monitoring, Emergency Alert SystemAbstract
Road accidents are one of the leading causes of fatalities worldwide, primarily due to delayed emergency response and lack of real-time monitoring systems. This paper presents AcciAlert, an intelligent accident detection and alert system that leverages deep learning and computer vision techniques for real-time traffic monitoring. The system utilizes a pre-trained SSD MobileNet V1 model with the MS COCO dataset to detect vehicles and analyze their motion patterns in video streams. By applying object tracking and collision detection algorithms, the system identifies abnormal events indicative of accidents. Upon detection, automated alerts are generated and transmitted to emergency services with location details, ensuring rapid response. The proposed system aims to enhance road safety, reduce response time, and improve survival rates. Experimental results demonstrate high accuracy and reliability in detecting accidents under various traffic conditions.
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