Enhancing Road Safety through Automated Pothole Detection (KEY IJP************999)

• N. Dyuthi Reddy,J. Buvaan,E. Sree Harsha

Abstract

Potholes are a major cause of accidents and injuries on road, and there is a growing need for new technologies to improve road safety. Object detection using deep learning is a promising new approach that can be used to identify potholes. In this project, we will develop a system for road safety implementation using object detection in deep learning. The system will use a camera to capture images of road, and a deep learning model will be used to detect objects such as potholes, depth and size. The system will then be able to generate alerts if it detects any of the objects. The system will be evaluated on a data set of images from real-world environments. We will measure the accuracy of the system in detecting objects and hazards and we will also evaluate the system's ability to generate timely alerts. The results of this project will demonstrate the feasibility of using object detection in deep learning for road safety implementation. The system has the potential to significantly improve safety on roads by reducing the number of accidents and injuries.