**Executive Summary**
Indian Railways is deploying advanced AI and Machine Learning technologies to enhance safety and operational efficiency through smart monitoring. Key systems include TRI-Netra for adverse weather visibility, Wheel Impact Load Detectors, and Online Monitoring of Rolling Stock. A new Rail Tech Policy, adopted on February 26, 2026, aims to expedite the adoption of innovative AI-driven solutions.
**Key Points / Main Content**
* **System Deployments and Development:**
* **TRI-Netra System:** Under development by RDSO to assist loco pilots by providing enhanced vision during foggy and adverse weather conditions, utilizing optical cameras, infra-red cameras, and ranging devices with AI.
* **Wheel Impact Load Detector (WILD):** 24 systems are installed for real-time monitoring of wheel and track impact to identify defective wheels.
* **Online Monitoring of Rolling Stock (OMRS):** 25 systems are installed for real-time monitoring of wheel and bearing health.
* **Machine Vision Inspection System (MVIS):** Deployed on a pilot basis, with systems in Northeast Frontier Railway, DFCCIL, and South East Central Railway for detecting hanging, loose, or missing components of moving trains. A MoU is in place for inducting four additional MVIS for freight stock. RDSO is also developing MVIS for rolling stock.
* **Integrated Track Monitoring Systems (ITMS):** 3 systems are deployed for AI-based inspection and monitoring of track components, utilizing machine learning and image processing to detect defects and aid in maintenance planning.
* **Drone-based Monitoring of Overhead Equipment (OHE):** Piloted in Raipur Division with thermal imaging, and development of AI/ML-enabled aerial inspection is underway with IIT Madras.
* **Rail Tech Policy:**
* Adopted on February 26, 2026, to support the development of cost-effective, implementable, and scalable AI and data-driven solutions.
* A portal (https://railtech.indianrailways.gov.in) has been launched to facilitate participation from innovators and startups.
* Key features include single-stage proposal submissions, provision for self-initiated challenges, 50:50 cost-sharing for prototype development and trials, and grants for extended trials or scale-up.
**Impact Analysis**
* **Loco Pilots**
* **Impact:** Enhanced vision and safety during adverse weather conditions through systems like TRI-Netra.
* **Action Required:** To utilize and provide feedback on new vision-assistance systems.
* **Rolling Stock Operations**
* **Impact:** Improved monitoring of wheel and bearing health through WILD and OMRS systems, leading to enhanced safety and reliability.
* **Action Required:** To ensure rolling stock components are compatible with monitoring systems and to act on any detected defects.
* **Track Maintenance**
* **Impact:** More efficient and effective track inspection and monitoring through ITMS, leading to improved track reliability and operational efficiency.
* **Action Required:** To utilize data from ITMS for proactive and planned track maintenance.
* **Innovators and Startups**
* **Impact:** New avenues for collaboration and funding for developing and implementing AI-driven solutions for Indian Railways.
* **Action Required:** To submit proposals through the Rail Tech portal for self-initiated challenges or in response to specific needs.
Key Entities Referenced
Rail Tech Policy: A new policy adopted by Indian Railways to support the development and adoption of cost-effective, implementable, and scalable AI and data-driven technology solutions, including a dedicated portal for innovators and startups.
Indian Railways: The national railway company of India, deploying advanced AI and Machine Learning devices for safety and operational efficiency.
RDSO: Research Designs and Standards Organisation, responsible for developing systems like TRI-Netra and MVIS for Indian Railways.
DFCCIL: Dedicated Freight Corridor Corporation of India Limited, a joint venture with Indian Railways for freight stock development.
IIT Madras: Indian Institute of Technology Madras, collaborating with Indian Railways on drone-based aerial inspection technology.
Ministry of Railways
Indian Railways Deploys Advance AI & Machine
Learning Devices to Enhance Safety and its
Operational Efficiency by Adopting Smart
Monitoring
TRI-Netra System Being Developed by RDSO to Assist Loco
Pilots with Enhanced Vision During Foggy and Adverse
Weather Conditions
24 Wheel Impact Load Detector (WILD) Systems and 25
Online Monitoring of Rolling Stock (OMRS) Systems Installed
for Real-time Monitoring of Wheel and Bearing Health
Machine Vision Inspection System (MVIS) Deployed on Pilot
Basis; 3 Systems in Northeast Frontier Railway, 2 in DFCCIL
and 1 in South East Central Railway
3 Integrated Track Monitoring Systems (ITMS) Deployed for
AI-based Inspection and Monitoring of Track Components
Drone-based Thermal Monitoring of Overhead Equipment
Piloted in Raipur Division; AI-enabled Aerial Inspection Under
Development with IIT Madras
Rail Tech Policy and Portal to Fast-Track AI-Driven, Scalable
Innovations
Posted On: 12 MAR 2026 12:39PM by PIB Delhi
Technological improvement in Indian Railways (IR) is a continuous process. Some major technologies
deployed/piloted over IR are as follows:
Machine Vision Inspection System (MVIS): MVIS is an Artificial Intelligence (AI)/ Machine
Learning (ML) based system which generates alerts on detecting any hanging, loose or missing
components of moving trains. Three (03) MVIS have been installed in Northeast Frontier Railway,
two (02) in Dedicated Freight Corridor Corporation of India Limited (DFCCIL) and one (01) in
South East Central Railway on pilot basis for freight stock. Further, a MoU has been signed betweenIR and DFCCIL to induct four (04) MVIS over IR network for freight stock. Also, Research
Designs and Standards Organisation (RDSO) has taken up development of MVIS for rolling stock
in collaboration with industry through an Expression of Interest (EoI).
Wheel Impact Load Detector (WILD): WILD is a way-side inspection system that measures the
impact of wheel on track to identify the defective wheel in Rolling Stock. 24 such systems are
installed over IR.
Online Monitoring of Rolling Stock (OMRS): OMRS is a way-side inspection system which
monitors the health of bearing & wheel of Rolling Stock. 25 such systems are installed over IR out
of which one (01) OMRS is installed at Sirpur Kaghaz nagar /Secunderabad Division in South
Central Railway.
Integrated Track Monitoring Systems (ITMS): ITMS are deployed for comprehensive inspection
and monitoring of Railway tracks. The ITMS utilizes machine learning and image processing to
monitor and detect defects in railway track components such as rails, sleepers, and fastenings. The
data from ITMS is analysed for urgent and planned maintenance of track. Presently three (03) ITMS
are deployed for track recording and monitoring of IR track. It helps in better track maintenance
planning, enhanced safety, improved reliability of track assets and operational efficiency.
Drone based monitoring of Overhead Equipment: Drone based monitoring with thermal imaging of
Overhead Equipment (OHE) has been taken up in Raipur division on pilot basis. Further, IR in
association with IIT Madras, has taken up development of a Drone based aerial inspection of
Overhead Equipment (OHE) which will also analyse the captured data using AI/ML.
TRI-Netra: RDSO has taken up development of TRI-Netra (Terrain Imaging for Locomotive
Drivers - Infra-Red, Enhanced Optical & Ranging Device Assisted) for assisting the Loco pilots
during foggy, rainy and inclement weather. This system comprises of optical cameras, infra-red
camera and ranging devices (e.g. Radar/Lidar) & Al to create a real-time, enhanced vision system
for assisting Loco pilots.
Rail Tech Policy: Further, to support the development of cost-effective, implementable and scalable
solutions, including those based on AI and data-driven technologies, a new policy called the Rail Tech
Policy has been adopted on 26.02.2026 by IR and a portal (https://railtech.indianrailways.gov.in) has
been launched to facilitate participation of innovators and startups.
The proposed Rail Tech Policy incorporates the following key features:
Single-stage detailed submission of proposals by the Innovator.
Provision for submission of proposals for self-initiated challenges by the Innovator on the Rail Tech
Portal.
Provision for funding on 50:50 cost-sharing basis between Indian Railways and the Innovator, with
the maximum grant for prototype development and trials.
Grant offered for extended trials or scale-up
The above proposed Policy will facilitate early adoption of new technologies in Indian Railways.
This information was provided by the Union Minister for Railways, Information & Broadcasting and
Electronics & Information Technology, Shri Ashwini Vaishnaw, in a reply to questions in Lok Sabha.
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Dharmendra Tewari/ Ritu Raj/ Manik Sharma
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