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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM48619
Volume:
9 |
5 |
May 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Road accidents have emerged as a critical global concern, resulting in significant loss of life, injuries, and property damage. Timely detection and response to such incidents can significantly reduce fatalities and improve emergency services. In this research, we propose an intelligent road accident detection system utilizing Artificial Intelligence (AI) and Machine Learning (ML) approaches. The system employs advanced computer vision techniques integrated with real-time video surveillance for accurate accident detection. Deep Learning models, particularly Convolutional Neural Networks (CNN), are used for object detection, motion analysis, and abnormal behavior identification on roads. This paper presents a detailed methodology, a literature review of existing systems, and a proposed architecture for efficient accident detection and notification systems. The findings suggest that AI-driven solutions can revolutionize road safety management systems.
KEYWORDS
Publication Date
5/26/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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