Integrating Google Maps and Deep Learning in Path Hole Detection Alert System

The project proposes a novel solution for pothole detection and alerting by integrating YOLOv5, Google Maps, and an email reporting system. YOLOv5, a state-of-the-art object detection algorithm, is employed to accurately identify potholes from live camera feeds. The system seamlessly integrates with Google Maps, allowing real-time visualization of detected potholes on the map interface. Furthermore, it incorporates an email reporting system, automatically generating detailed reports containing location information, images, and severity levels of detected potholes. This integration enhances road maintenance efficiency by providing authorities with timely and precise information about pothole locations. By leveraging cutting-edge technology, this project aims to contribute to safer and more efficient road infrastructure management, ultimately enhancing road safety and minimizing vehicle damage caused by potholes.