AI, ML Technologies Deployed To Enhance Railway Safety And Asset Monitoring, Says Minister

New Delhi, Mar 12 (KNN) The national transporter has deployed a range of artificial intelligence (AI) and machine learning (ML) based technologies to enhance operational safety, improve monitoring of railway assets and strengthen overall efficiency across the network, Union Railway Minister Ashwini Vaishnaw said in Lok Sabha.

In written reply to a question, the minister said that the national transporter is adopting advanced smart monitoring systems for rolling stock, tracks and overhead equipment as part of its ongoing technology modernisation programme.

Among the key technologies introduced is the Machine Vision Inspection System (MVIS), an AI and ML-based platform designed to detect hanging, loose or missing components in moving trains. The system generates automated alerts to enable timely intervention and prevent potential safety risks.

Currently, three MVIS systems have been installed in the Northeast Frontier Railway, two in the Dedicated Freight Corridor Corporation of India Limited (DFCCIL) network and one in the South East Central Railway on a pilot basis for freight trains. 

Indian Railways has also signed a memorandum of understanding with DFCCIL to deploy four additional MVIS systems across the rail network. The Research Designs and Standards Organisation (RDSO) is also working with industry partners to further develop the system for broader rolling stock monitoring.

Indian Railways has also installed 24 Wheel Impact Load Detector (WILD) systems, which are wayside inspection systems used to measure the impact of wheels on tracks in order to detect defective wheels in rolling stock.

Additionally, 25 Online Monitoring of Rolling Stock (OMRS) systems have been deployed to monitor the health of bearings and wheels in real time. One such system has been installed at Sirpur Kagaznagar in the Secunderabad Division of South Central Railway.

For track infrastructure monitoring, three Integrated Track Monitoring Systems (ITMS) have been deployed. These systems utilise machine learning and image processing to detect defects in track components such as rails, sleepers and fastenings. The data generated helps railway authorities plan urgent as well as preventive maintenance to improve reliability and operational efficiency.

Indian Railways has also initiated drone-based monitoring of overhead equipment using thermal imaging technology. The system is currently being piloted in the Raipur Division. 

Another major initiative under development is the TRI-Netra system (Terrain Imaging for Locomotive Drivers – Infra-Red, Enhanced Optical and Ranging Device Assisted). 

Developed by RDSO, the system integrates optical and infrared cameras with radar or lidar-based ranging devices to provide enhanced real-time vision to locomotive pilots during fog, rain and other adverse weather conditions.

(KNN Bureau)