Real-Time Road Traffic Incident Management System Using CNN

Millions of people die or are injured due to traffic accidents each year, where delayed responses to emergency situations are one of major causes of fatal incidents. To address the issue, this project proposes a Machine learning (ML) based Road Accident Detection and Notification System that can help reduce response time in accidents. This system makes use of CCTV datasets communication in the identification of accidents at real world. The system collects detailed data when an accident happens, such as photo of the location, intensity of impact, etc. Convolutional Neural Networks (CNN), especially convolutional deep learning algorithms, investigate the images to detect accidents perfectly. Once detected, it automatically alerts nearby hospitals, police stations and other emergency support teams with the system reduces delay by ensuring rapid deployment of Medical and Rescue teams.