Road Radar: Integrated Road Monitoring and Maintenance System

Potholes pose a significant threat to road safety in India, contributing to serious traffic accidents. To address this issue, a camera-based system mounted in cars is proposed to detect any road irregularities in real time. The system utilizes You Only Look Once (YOLO) object detection algorithm to identify road irregularities, followed by image processing algorithms to refine detections and improve accuracy. Additionally, Convolutional Neural Networks (CNN) are employed to classify the severity of detected potholes. Real-time notifications are displayed on the dashboard to alert the driver when an obstacle is detected, and a buzzer inside the car sounds when the vehicle approaches an obstruction, in this case, ten meters, prompting the driver to slow down while simultaneously notifying the maintenance team about the pothole’s location. A graph will be generated which will include location of the pothole versus area of the pothole. The biggest pothole will be detected, then the maintenance team will try to make this location their priority and will attempt to fix that first in order to prevent major accidents. At the same time, the location that gets the highest number of notifications will be viewed and made a priority. The primary objective is to enhance road safety by alerting drivers to hazards like potholes in real-time, especially prevalent in India. Through YOLO, image processing, and CNN integration, the system aims to decrease accidents, promote cautious driving, and possibly reroute to safer paths, mitigating pothole-related accidents and enhancing overall road safety nationwide.