Indian Railways deploys AI systems to monitor trains, tracks, and overhead equipment
Indian Railways is installing machine learning-based monitoring systems across its network to detect equipment failures before they cause safety issues. The ministry shared details of these deployments in parliament, outlining a strategy to catch problems in moving trains, track infrastructure, and electrical systems.
Detection systems now in operation
The Machine Vision Inspection System (MVIS) uses computer vision to spot hanging, loose, or missing components on trains as they move. Indian Railways has tested the system at six locations-three in the Northeast Frontier Railway, two under the Dedicated Freight Corridor Corporation, and one in the South East Central Railway. An agreement between Indian Railways and the freight corridor operator will add four more MVIS installations.
Twenty-four Wheel Impact Load Detector systems now identify defective wheels by measuring the force wheels exert on tracks. The railways operates 25 Online Monitoring of Rolling Stock systems that track bearing and wheel health in real time.
For track inspection, three Integrated Track Monitoring Systems use machine learning and image analysis to find defects in rails, sleepers, and fastenings. The data feeds maintenance planning for both urgent repairs and scheduled work.
Newer technologies in testing and development
The Raipur Division is piloting drone-based thermal monitoring of overhead electrical equipment. The system identifies potential failures through heat signatures. Indian Railways is also working with IIT Madras to develop an AI-enabled drone system that analyzes aerial images to support predictive maintenance.
A system called TRI-Netra, developed by the Research Designs and Standards Organisation, will assist train drivers during poor visibility. It combines optical cameras, infrared sensors, and radar or lidar to improve sight lines in fog, rain, and other adverse conditions.
New policy opens technology development to startups
Indian Railways approved a Rail Tech Policy in February 2026 and launched a dedicated portal for technology submissions. The policy targets scalable, cost-effective solutions, particularly those using AI and data analysis.
Innovators and startups can propose technologies through the portal. Indian Railways will split prototype development and trial costs 50-50 with successful applicants and support extended testing and scaling of proven solutions.
These initiatives sit within a broader shift toward AI Agents & Automation across infrastructure sectors. For IT professionals evaluating these systems, understanding how AI for IT & Development applies to operational technology environments is increasingly relevant to career development in infrastructure roles.
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