Road Guard: AI-Powered Road Damage Detection and Reporting System

Potholes pose a significant challenge to road safety and infrastructure maintenance, demanding efficient solutions for detection and reporting. This paper presents an automated system for real-time pothole detection and reporting, leveraging the YOLOv8 object detection model and GPS integration for accurate location tracking. A Flask-based web application provides an organized platform to manage detected pothole data, classify severity levels such as Critical or Average, and store information in a JSON file for persistent access. Additionally, an interactive map feature enables authorities to filter, view, and manage pothole records efficiently. The proposed system demonstrates a practical approach to improve road condition monitoring and maintenance.