Smart Pavement Repair Bot with IoT and Machine Learning Integration

Potholes on road surfaces pose significant challenges, leading to vehicle damage, traffic inefficiencies, and increased safety risks. Conventional pothole detection and repair methods are labor-intensive, time-consuming, and costly. This project presents an autonomous Pothole Detection and Refilling Robot that utilizes Internet of Things (IoT) and Machine Learning (ML) technologies to automate the process of pothole identification and repair. The system incorporates ultrasonic sensors for detecting road surface anomalies and a camera, integrated with ML algorithms, for visual confirmation and classification of potholes. The robot wirelessly transmits detection data via Zigbee modules to a central monitoring system, facilitating real-time updates. Upon pothole detection, the robot autonomously engages a mechanical refilling system to dispense filler material, effectively restoring the road surface. By combining IoT for data communication, sensor-based detection, and ML-based image processing, the system provides a cost-effective and scalable solution for road maintenance. This approach reduces human intervention, optimizes repair efficiency, and enhances road safety by enabling continuous, autonomous monitoring and maintenance of road infrastructure.