Smart Road Condition Monitoring and Optimal Routing System Using Yolo V11

Abstract

Abstract—This project tackles the urgent problem of potholes on roads through the creation of areal-time pothole detection and map-ping system. Making use of the YOLO V11 deep learning algorithm, our system analyzes video  feeds  to  detect  potholes on the road surface accurately and efficiently. This allows for real-time alerts to drivers, enabling them to respond quickly and evade accidents. In addition, the system produces a dynamic map of identified potholes, constantly refreshed with new information. This map not only gives a visual display of road condition but also feeds into an optimal routing module. The routing system takes advantage of this real-time information to recommend  safer and more efficient routes, leading drivers  away  from  roads with high densities of potholes.Aimed for flexibility and integration into diverse vehicle platforms, the system maximizes real-time performance for efficient operation in dynamic driving conditions. Future work will target increased detection accuracy under varied conditions to further optimize the reliability and efficiency of the system. This project is a major breakthrough    in road safety technology, providing an end-to-end solution for pothole detection and avoidance.