AI-Driven Pavement Repair Bot with IoT Connectivity

Road surface potholes provide serious problems since they can cause car damage, inefficient traffic, and elevated safety hazards. Traditional techniques for detecting and fixing potholes are expensive, time-consuming, and labor-intensive. This project introduces an autonomous Pothole Detection and Refilling Robot that automates pothole identification and repair by leveraging Internet of Things (IoT) and Machine Learning (ML) technology. The device includes a camera that is integrated with machine learning algorithms to visually confirm and classify potholes, as well as ultrasonic sensors for detecting abnormalities in the road surface. Real-time updates are made possible by the robot's wireless transmission of detection data to a central monitoring system using Zigbee modules. The robot automatically activates a mechanical refilling system to dispense filler material upon detecting a pothole, therefore repairing the road surface. Using IoT in conjunction with data communication the technology offers a scalable and reasonably priced approach to road repair through sensor-based detection and machine learning-based picture processing. This method allows for continuous, autonomous monitoring and maintenance of road infrastructure, which minimizes human intervention, maximizes repair efficiency, and improves road safety.