Published Paper Details:

Railway safety depends on constantly monitoring the tracks, because unnoticed cracks or obstacles can lead to serious accidents. This paper introduces an intelligent Railway Track Obstacle and Crack Detection System designed to improve safety through automation. The system uses sensors, image processing, and machine learning to detect cracks and obstacles in real time. IR and ultrasonic sensors help in identifying cracks, while object detection techniques recognize any obstacles on the track. The system also includes GPS and GSM modules to track the exact fault location and send instant alerts to the authorities for quick maintenance. Experimental results show that the system provides high detection accuracy in different environmental conditions. Overall, the proposed model is cost-effective, efficient, and scalable. It reduces the need for manual inspection and increases the overall reliability of railway operations.