Road Damage Assessment

Abstract

In this research, the emphasis is placed on the vital function of roadway systems in spurring economic growth, connecting different communities, and ensuring access to crucial services like education and healthcare. The study identifies several key factors contributing to the wear and tear of road infrastructures, such as extreme weather conditions, high traffic volumes, suboptimal construction techniques, and lack of regular upkeep. Specifically, the occurrence of potholes is highlighted as a major concern, leading to not only discomfort for commuters but also potential vehicle damage and increased risk of traffic incidents. To address this, the research proposes a novel approach that involves monitoring the flow and categorizing vehicles by their weight to gauge their impact on road surfaces. For the accurate identification and mapping of potholes, the study utilizes the advanced capabilities of the YoloV8 algorithm. This technique is further enhanced by integrating it with a mobile application and Google Maps, enabling a comprehensive and city-wide application of the pothole detection system. Roads are a critical component of a nation's infrastructure, but they are subject to deterioration over the time due to various factors. Road damage assessment software has emerged as an innovative solution to monitor, evaluate, and prioritize road maintenance needs. This report provides a comprehensive overview of road damage assessment software, starting with an introduction, followed by a literature survey, limitations of the existing systems, problem statement, proposed system, framework, design details, methodology, experimental setup, details of the database, performance evaluation, software and hardware setup, future work, and references. Key Words: Road , Potholes , Damage , deep learning, Accidents, YOLOv8