Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Vol 9 No 3 (2025): Volume 9, Issue 3, March 2025 | Pages: 314-319
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 19-04-2025
In India, accidents are a major cause of death. Over 80% of accident fatalities are caused by delayed assistance to victims. Accident victims can be left unattended for extended periods on lightly trafficked highways. To address this issue, we propose a system that uses deep learning to detect accidents from live CCTV video feeds. Each video frame is processed by a Convolutional Neural Network (CNN) trained to distinguish between accident and non-accident scenarios. CNNs are known for their speed, accuracy, and reduced preprocessing requirements, making them suitable for this task. With smaller datasets, CNN-based image classifiers have achieved over 95% accuracy.
Real Time, Accident Detection System, CNN, Convolutional Neural Network
Nadiminti Pulikonda, Dr. Varada Ramanath, Regati Rajashekar, Shaik Masood vali, & Saragaboina Naresh babu. (2025). Real Time Accident Detection System using CNN. International Research Journal of Innovations in Engineering and Technology - IRJIET, 9(3), 314-319. Article DOI https://doi.org/10.47001/IRJIET/2025.903045
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