Road Accident Detection Using AI and ML.

Abstract - 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- Road Accident Detection, Artificial Intelligence, Machine Learning, Deep Learning, Convolutional Neural Network, Real-time Monitoring, Smart Transportation.

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-05-26
DOI
https://doi.org/10.55041/ijsrem48619
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Road Accident Detection Using AI and ML.

Aryan Salunke
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Traffic Prediction and Management Techniques
article

Road Accident Detection Using AI and ML.

Aryan Salunke
article en

Abstract

Abstract - 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- Road Accident Detection, Artificial Intelligence, Machine Learning, Deep Learning, Convolutional Neural Network, Real-time Monitoring, Smart Transportation.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(05)
Openalex Percentile: Top 88%
Traffic Prediction and Management Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.