Published Paper Details:

Potholes are areas of road surface that have cracked, worn away, and eventually formed a hole. Potholes make a ride bumpy and potentially dangerous. They can damage vehicle tires and even affect the alignment of a vehicle's wheels. With advancing urbanization, roads serve as a most important way of communication. But the increasing potholes on the roads pose a bigger danger towards public safety. Identifying and locating road potholes promptly has become a major challenge for urban construction. To address the need for improved infrastructure management, the aim of the project is to propose a pothole detection and alert system using the YOLOv8 object detection algorithm on urban road images. To enable accurate segmentation of fine-grained features, this project optimized the PothNet, which enables the segmentation head to generate high-quality masks for more accurate prediction. The proposed system serves a dual purpose, providing timely alerts to both car drivers traversing the same route and municipal authorities responsible for road maintenance. By leveraging intelligent algorithms, the system not only detects potholes but also identifies road segments in urgent need of repair. This holistic approach helps address imbalances in infrastructure maintenance efforts across cities, promoting a more equitable distribution of resources. The intelligent Pothole Detection and Alert System contribute significantly to enhancing road safety and fostering a smoother driving experience.