Railways Expand AI-Based Predictive Maintenance Systems

08 Dec 2025 CW Team

Indian Railways continues to advance technological modernisation, with several Artificial Intelligence-based predictive maintenance applications now being implemented across the network.

Pilot projects using AI-driven predictive maintenance for signalling systems are under way at selected stations to evaluate their effectiveness. These trials aim to generate measurable outputs, including standardised failure-prediction logic and automated alert mechanisms.

An AI-enabled Intrusion Detection System (IDS) using Distributed Acoustic Sensing (DAS) has been deployed across a 141-route-kilometre section of Northeast Frontier Railway to detect the presence of elephants on the tracks. Alerts are generated for loco pilots, station masters and control rooms to facilitate timely preventive action. Tenders have also been awarded for extending this system to a further 981 route kilometres across Indian Railways.

Indian Railways has also adopted advanced technologies such as the Online Monitoring of Rolling Stock System (OMRS) and the Wheel Impact Load Detector (WILD) to support predictive maintenance of rolling stock.

In July 2025, a Memorandum of Understanding was signed with the Dedicated Freight Corridor Corporation of India Limited for the induction of a Wayside Machine Vision-based Inspection System (MVIS). Driven by AI and machine learning, MVIS detects hanging parts or missing components in moving trains.

Another MoU with the Delhi Metro Rail Corporation provides for the introduction of the Automatic Wheel Profile Measurement System (AWPMS). This non-contact technology measures train wheel profiles automatically, offering real-time data on wheel geometry and wear.

This information was provided by Shri Ashwini Vaishnaw, Union Minister for Railways, Information & Broadcasting and Electronics & Information Technology, in a written reply in the Rajya Sabha.

Indian Railways continues to advance technological modernisation, with several Artificial Intelligence-based predictive maintenance applications now being implemented across the network. Pilot projects using AI-driven predictive maintenance for signalling systems are under way at selected stations to evaluate their effectiveness. These trials aim to generate measurable outputs, including standardised failure-prediction logic and automated alert mechanisms. An AI-enabled Intrusion Detection System (IDS) using Distributed Acoustic Sensing (DAS) has been deployed across a 141-route-kilometre section of Northeast Frontier Railway to detect the presence of elephants on the tracks. Alerts are generated for loco pilots, station masters and control rooms to facilitate timely preventive action. Tenders have also been awarded for extending this system to a further 981 route kilometres across Indian Railways. Indian Railways has also adopted advanced technologies such as the Online Monitoring of Rolling Stock System (OMRS) and the Wheel Impact Load Detector (WILD) to support predictive maintenance of rolling stock. In July 2025, a Memorandum of Understanding was signed with the Dedicated Freight Corridor Corporation of India Limited for the induction of a Wayside Machine Vision-based Inspection System (MVIS). Driven by AI and machine learning, MVIS detects hanging parts or missing components in moving trains. Another MoU with the Delhi Metro Rail Corporation provides for the introduction of the Automatic Wheel Profile Measurement System (AWPMS). This non-contact technology measures train wheel profiles automatically, offering real-time data on wheel geometry and wear. This information was provided by Shri Ashwini Vaishnaw, Union Minister for Railways, Information & Broadcasting and Electronics & Information Technology, in a written reply in the Rajya Sabha.

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