Design of an automatic obstacle detection system for trains

Abstract

This project aims to develop an automated obstacle detection system for trains. Utilizing advanced machine learning algorithms and computer vision methods, the system will process real-time data from onboard sensors to detect potential track obstructions. The automated model will improve train safety and efficiency by delivering timely alerts and aiding in proactive obstacle avoidance. By incorporating innovative technologies, this project intends to advance rail transportation and tackle crucial safety issues related to railway track obstacles.