Indian Railways has announced a significant technological advancement with the launch of a Machine Vision-based Inspection System (MVIS) designed to detect hanging parts or missing components in moving trains. The AI- and ML-driven system aims to bolster operational safety, reduce manual inspections, and prevent potential accidents across the rail network.
As part of a pilot initiative, four MVIS units are being installed at strategic locations including Tughlakabad in Delhi, Mauda in Nagpur, Visakhapatnam in Vizianagaram, and Toranagallu in Hubballi. Officials stated that, once successfully validated, the system will be deployed across all railway zones, representing a transformative step towards modernising India’s rail infrastructure. The MVIS captures high-resolution images of the under-gear of trains in motion, analysing them in real time for anomalies such as loose, hanging, or missing components. Alerts are automatically generated to ensure rapid response and preventive maintenance, reducing the reliance on manual inspections and minimising service disruptions.
The Dedicated Freight Corridor Corporation of India Limited (DFCCIL) has been tasked with the procurement, installation, testing, and commissioning of the pilot systems. Experts suggest that the adoption of AI and ML technology in this context represents a pioneering application for the Indian Railways, with the potential to significantly enhance safety standards and operational efficiency. Indian Railways has previously introduced technology-driven solutions such as the Online Monitoring of Rolling Stock System (OMRS) and Wheel Impact Load Detector (WILD), designed for predictive maintenance of train assets. MVIS complements these efforts by introducing real-time monitoring capabilities for operational safety, particularly for moving trains.
Officials noted that AI/ML models have already improved passenger services through platforms like Rail Madad and the Passenger Reservation System, while also optimising freight operations by predicting estimated train arrival times and unloading durations. The MVIS initiative is expected to extend this technological ecosystem to operational safety, aligning with broader goals of creating sustainable, efficient, and equitable railway services. This development also reflects a strategic shift towards integrating cutting-edge AI solutions into India’s rail network, ensuring safer and more reliable journeys for millions of daily passengers. By pre-emptively detecting potential equipment failures, the system reduces accident risk and fosters confidence in rail travel.
Railway authorities emphasised that these pilot installations will undergo rigorous testing before any phased expansion is considered, highlighting a careful approach to technology adoption that balances innovation with safety assurance.
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