Authors - Ashwini Jarali, Sanskruti Lad, Snehal Kavathekar, Prajwal Lalpotu, Shreya Jadhav Abstract - Potholes on roads significantly impact safety and road infrastructure, leading to accidents and increased vehicle damage. Timely detection and repair are crucial to address these issues effectively. This paper presents an AI-based system for automated pothole detection and reporting, aimed at improving pothole management for road maintenance authorities. The system uses the YOLO (You Only Look Once) object detection model to accurately identify potholes in real-time road imagery, combined with GPS for precise localization. Detected potholes are automatically reported to the relevant authorities via email, ensuring swift corrective action. The YOLO model is trained on a diverse dataset of pothole images, achieving high detection accuracy across various pothole sizes and shapes. Additionally, the system tracks the status of reported potholes to ensure repairs are completed. This solution enhances road safety and reduces manual effort, providing a comprehensive approach to modern road maintenance.
