Abstract:
The railway infrastructure maintenance is paramount for ensuring efficient and
safe operations across vast distances with minimal human intervention. The Railway
Tracks Checking Rover emerges as a pivotal solution designed to traverse railway tracks,
identifying faults in rails, sleepers, pads, clips, and detecting unwanted objects along the
track. This research introduces a rover equipped with cameras and onboard machine
learning algorithms to capture and process real-time video data, swiftly detecting track
anomalies. In the event of hazards, pertinent information including video footage, sensor
data, and distance from the nearest station is promptly relayed to the control room for
swift action. Additionally, night vision flashers and ultrasound distance sensors enhance
visibility and measure rail heights, mitigating risks and ensuring optimal track conditions.
Utilizing GSM modules and long-range radio transmitters for data transmission, the rover
facilitates seamless communication of sensor data and video feeds to the control center,
ensuring a timely response to potential threats. The Railway Tracks Checking Rover
heralds a new era in railway track maintenance, offering a cost-effective, efficient, and
technologically advanced solution. Its implementation promises to bolster railway safety,
reduce maintenance expenditures, and enhance the overall reliability of railway
infrastructure, thereby optimizing railway operations and ensuring passenger safety.
