GlobalData
Mon, Jul 14, 2025, 11:49 AM 2 min read
Indian Railways has signed a memorandum of understanding (MoU) with the Dedicated Freight Corridor Corporation of India Limited (DFCCIL) to implement an AI-based train safety system designed to improve the monitoring of rolling stock health.
This move signifies a leap towards integrating advanced technologies for service efficiency and maintenance automation in the rail sector.
The MoU was signed by India's Ministry of Railways (Railway Board) project and development director Sumit Kumar and DFCCIL GGM (Mechanical) Jawahar Lal at Rail Bhawan in New Delhi.
Witnessing the event were DFCCIL managing director Praveen Kumar and other senior officials.
The machine vision-based inspection system (MVIS) utilises artificial intelligence and machine learning (AI/ML) to capture high-resolution images of the under-gear of moving trains, automatically detecting anomalies such as hanging, loose, or missing components.
The system then promptly alerts the relevant authorities in real-time, enabling quick response and preventive measures. It promises to significantly boost train operation safety, reduce manual inspections, and prevent accidents and service disruptions.
DFCCIL's responsibilities under the MoU include the procurement, supply, installation, testing, and commissioning of four MVIS units.
The initiative is part of Indian Railways' wider goal of integrating intelligent systems into the railway ecosystem.
The signing of this MoU is a crucial step towards the digital transformation of rail safety and the development of a future-ready rail infrastructure.
In a related development, the Digital India Bhashini Division (DIBD) and the Centre for Railway Information Systems (CRIS) have signed an MoU to create multilingual AI solutions for Indian Railways.
The initiative will support passenger interactions in 22 Indian languages, advancing linguistic inclusivity and digital transformation.
"Indian Railways signs MoU with DFCCIL to install AI/ML-based inspection system" was originally created and published by Railway Technology, a GlobalData owned brand.
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