Enhancing Road Safety with Machine Learning- based Pothole Detection

Abstract: The goal of this project endeavours to enhance road safety through a machine learning-based pothole detection system. The primary objective is to develop an artificial intelligence solution that can accurately identify and analyse potholes on road surfaces, thereby contributing to proactive road maintenance and accident prevention. Employing advanced computer vision algorithms, the system focuses on detecting key features associated with potholes, utilizing joint point analysis for precise identification. Utilizing cutting-edge machine learning models, the program categorizes and classifies various pothole characteristics, ensuring comprehensive coverage of road conditions. The user-friendly interface of the system allows for seamless interaction, displaying detected potholes and providing specific information, such as their dimensions and potential impact on road safety. A key advantage of this AI pothole detection system lies in its ability to offer tailored feedback to users, facilitating prompt repairs and maintenance. By actively assisting in the identification and rectification of potholes, the technology transcends mere detection, significantly contributing to the overall improvement of road safety.