Deep Learning-Based Accident Detection and Ambulance Notification System for Saving Lives on Roads

Road traffic accidents are a leading cause of fatalities worldwide, with many lives lost due to delayed medical assistance. This research proposes a real-time accident detection and ambulance notification system leveraging deep learning. The system uses object detection models to identify accident victims lying on roads and notifies nearby government ambulances using GPS-based localization. The proposed method employs YOLOv8 for rapid object detection and OpenPose for pose estimation to confirm the victim's condition. Experimental results demonstrate the model's high accuracy and responsiveness in various scenarios, showing potential for saving lives by minimizing emergency response time.