Indian Railways Deploys AI And ML Systems To Enhance Safety

13 Mar 2026 CW Team

Machine Vision Inspection System (MVIS) deployments use AI to detect hanging, loose or missing components on moving trains; three MVIS are in Northeast Frontier Railway, two in Dedicated Freight Corridor Corporation of India Limited (DFCCIL) and one in South East Central Railway, and an MoU with DFCCIL will induct four MVIS for freight stock. Wheel Impact Load Detector (WILD) systems have been installed at 24 locations to identify defective wheels. Online Monitoring of Rolling Stock (OMRS) way-side systems monitoring bearing and wheel health are installed at 25 locations.

Integrated Track Monitoring Systems (ITMS) using machine learning and image processing are deployed for inspection of rails, sleepers and fastenings, with three ITMS recording track condition to support urgent and planned maintenance and improve asset reliability. Drone-based thermal monitoring of overhead equipment has been piloted in Raipur Division and a joint development with IIT Madras is under way to create AI-enabled aerial inspection and data analysis. These systems aim to reduce unplanned failures and support efficient maintenance planning.

A Rail Tech Policy adopted on 26 February 2026 and the Rail Tech Portal have been launched to fast-track scalable, cost-effective innovations and to facilitate participation by innovators and startups. The policy allows single-stage detailed submissions, self-initiated challenge proposals on the portal, and funding on a 50:50 cost-sharing basis between Indian Railways and the innovator with grants for prototype development, trials and scale-up. The ministry said the policy is intended to accelerate adoption of AI and data-driven technologies across the network.

Indian Railways has deployed and piloted artificial intelligence and machine learning systems to bolster safety and operational efficiency across its network. Research Designs and Standards Organisation (RDSO) is developing TRI-Netra (Terrain Imaging for Locomotive Drivers - Infra-Red, Enhanced Optical and Ranging Device Assisted) to assist loco pilots in foggy and adverse weather by integrating optical cameras, infra-red imaging and ranging sensors with AI. The initiative covers inspection, monitoring and predictive maintenance. The ministry has outlined pilots across multiple zones. Machine Vision Inspection System (MVIS) deployments use AI to detect hanging, loose or missing components on moving trains; three MVIS are in Northeast Frontier Railway, two in Dedicated Freight Corridor Corporation of India Limited (DFCCIL) and one in South East Central Railway, and an MoU with DFCCIL will induct four MVIS for freight stock. Wheel Impact Load Detector (WILD) systems have been installed at 24 locations to identify defective wheels. Online Monitoring of Rolling Stock (OMRS) way-side systems monitoring bearing and wheel health are installed at 25 locations. Integrated Track Monitoring Systems (ITMS) using machine learning and image processing are deployed for inspection of rails, sleepers and fastenings, with three ITMS recording track condition to support urgent and planned maintenance and improve asset reliability. Drone-based thermal monitoring of overhead equipment has been piloted in Raipur Division and a joint development with IIT Madras is under way to create AI-enabled aerial inspection and data analysis. These systems aim to reduce unplanned failures and support efficient maintenance planning. A Rail Tech Policy adopted on 26 February 2026 and the Rail Tech Portal have been launched to fast-track scalable, cost-effective innovations and to facilitate participation by innovators and startups. The policy allows single-stage detailed submissions, self-initiated challenge proposals on the portal, and funding on a 50:50 cost-sharing basis between Indian Railways and the innovator with grants for prototype development, trials and scale-up. The ministry said the policy is intended to accelerate adoption of AI and data-driven technologies across the network.

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