Abstract

Road maintenance and repair is a crucial aspect of ensuring safe and efficient transportation systems. One of the most common and persistent problems faced by road authorities is the detection and timely repair of potholes. Potholes are a significant road safety concern, causing accidents, vehicle damage, and traffic congestion. To address this issue, an innovative Pothole Detection and Filling Robot (PDFR) is proposed in this research. The PDFR employs Raspberry Pi for real-time image processing and deploys the YOLOv5 algorithm for efficient and accurate pothole detection. The utilization of Raspberry Pi in the PDFR system serves as a powerful and cost-effective computing platform for real-time image acquisition, processing, and decision-making. The Raspberry Pi's computational capabilities are leveraged to capture high-resolution images of road surfaces while the robot navigates. The acquired images are then processed through the YOLOv5 algorithm, enabling rapid and precise pothole identification