Enhancing Deep Learning to Improve Road Safety: An Accident Detection System

This advanced accident detection system significantly improves road safety by enabling timely identification of traffic incidents and rapid emergency response. Current road safety systems often fail to provide accurate and prompt detection of accidents, resulting in delayed emergency services and increased casualties. To address this issue, an advanced system utilizes Convolutional Neural Networks (CNNs) and the You Only Look Once (YOLO) model for real-time accident detection and classification. By analyzing RGB frames and incorporating optical flow data, this system effectively handles dynamic scenarios such as high-speed traffic, varying weather conditions, and complex vehicle movements. Furthermore, a Real-Time Notification feature integrates to automatically alert nearby hospitals and dispatch ambulances immediately upon detecting an accident. Training and testing use the dataset from Kaggle, which includes CCTV footage frames of accidents and non-accidents, ensuring robust performance. This system detects accidents in real- time and promptly sends notifications via email to alert nearby hospitals and dispatch ambulances.