Driving Efficiency And Safety the Digitisation of Railways and Predictive Maintenance

Indian Railways

Indian Railways has opted for the Internet of Things (IoT) to enhance the operation of their train services. One notable initiative is the implementation of a Real-Time Train Information System (RTIS), which utilizes GPS sensors mounted on locomotives to monitor the exact location of trains in real time.

By equipping approximately 50% of Indian Railways locomotives with RTIS/ REMMLOT devices, a staggering 14 million “events” are generated each day. To enhance train operations, Indian Railways is actively working on installing RTIS devices on all locomotives to leverage real-time data. This endeavor involves harnessing artificial intelligence (AI) to enhance the accuracy of estimated time of arrivals (ETAs) for trains, streamline locomotive entry and exit processes, optimize the placement and removal of goods trains in goods sidings, and improve train rescheduling.

Real-Time Train Information System (RTIS)

Indian Railways has implemented the Internet of Things (IoT) to automate the generation of train arrival and departure information. The manual process of charting running trains is expected to be replaced by the Control Office Application (COA). As part of the Real-Time Train Information System (RTIS) project, around 2,700 electric locomotives on the Indian Railways network have been equipped with satellite devices.

The RTIS locomotive device consists of two components: the indoor unit, installed in the locomotive cabin, and the outdoor unit, mounted on the locomotive roof. These components work together to form the RTIS locomotive device. By continuously receiving spatial coordinates and speed data from the satellite receiver, the RTIS application software within the locomotive’s device applies predefined logic to determine various train movement events, such as arrivals, departures, and run-throughs (ADR) at stations, as well as location updates along the route at 30-second intervals.

Railway digitisation encompasses various advancements and technologies, including:

  • Implementation of B-scan ultrasonic rail flaw detection systems (both non-stop and stop-and-verify) and track inspection conducted by automated high-speed test trains.
  • Integration of train control systems at levels 2 & 3 on high-density routes to enhance network capacity while maintaining safety standards.
  • Enhanced monitoring of personnel through the utilisation of locomotive-mounted video surveillance systems, both inside and outside the train.
  • Adoption of track-laying machines to mechanise construction processes.
  • Electrification initiatives facilitated by self-propelled overhead electrification laying trains.
  • Introduction of complete train scanners to enhance diagnostics and maintenance procedures.
  • Implementation of distributed power systems to optimise train operations by coordinating acceleration and deceleration.
  • Establishment of smart railway stations by incorporating access control measures at entry points.
  • Implementation of e-ticketing systems with additional features like infotainment and app-based services.
  • Utilisation of training simulators and Virtual Reality (VR) training systems to enhance personnel capabilities.

These measures aim to modernise and improve railway operations through the integration of digital technologies and innovative solutions.

Center for Railway Information System (CRIS): Revamping Technological advancements in Indian Railways: Recognizing the potential of contemporary emerging technologies, CRIS is incorporating advanced solutions such as Blockchain, Artificial Intelligence (AI), Machine Learning (ML), Big Data, Business Intelligence, Cloud Services (both private and public cloud), Agility, Chatbots, Internet of Things (IoT), Augmented Reality/Virtual Reality (AR/VR), and more. These technologies are being leveraged to carry out various tasks including Train Route Optimization, Capacity Enhancement, Prediction of Train Delays and Waitlist Clearance, Predictive Maintenance of Rail Assets, Energy Consumption Forecasting, and Train Timetable Optimization. By embracing these emerging technologies, CRIS is revolutionizing its solutions and introducing a new dimension to its services.

Various smart solutions enabled by IoT that have revolutionised energy efficiency in rail networks:

  • IoT-enabled Asset Monitoring and Maintenance: One of the key challenges faced by rail networks is the efficient monitoring and maintenance of assets, including trains, tracks, and signaling systems. IoT technology facilitates real-time monitoring of these assets, enabling predictive maintenance and minimising downtime. Sensors embedded in critical components can collect data on factors like temperature, vibration, and performance, providing insights into potential failures or inefficiencies. With this information, maintenance teams can proactively address issues, reducing the occurrence of breakdowns and optimising energy usage.
  • Energy Management and Optimisation: IoT-based energy management systems have revolutionised the way energy is consumed and optimised in rail networks. Smart meters and sensors deployed across the rail infrastructure monitor and collect real-time data on energy consumption, enabling operators to identify inefficiencies and implement strategies to reduce energy wastage. Additionally, advanced analytics and machine learning algorithms can analyse the collected data to generate actionable insights for optimising energy usage, such as identifying peak and off-peak demand periods and adjusting energy supply accordingly. By optimising energy consumption, rail networks can reduce their overall carbon emissions and operational costs.
  • Intelligent Traffic Management: Efficient traffic management plays a crucial role in reducing energy consumption in rail networks. IoT-enabled sensors and communication systems enable real-time monitoring of train movements, allowing for precise scheduling and routing. By analysing factors like passenger demand, traffic congestion, and weather conditions, intelligent traffic management systems can optimise train schedules, reduce idling time, and minimise unnecessary stops. This results in smoother operations, reduced energy consumption, and improved overall efficiency.


  • Passenger Experience and Engagement: Enhancing the passenger experience while promoting energy efficiency is a key focus for rail networks. IoT technologies offer innovative solutions to achieve this goal. Smart sensors installed in trains and stations can collect data on passenger occupancy, temperature, and air quality. This information can be utilised to optimise HVAC systems, ensuring comfortable conditions for passengers while minimising energy usage. Furthermore, IoT-based mobile applications can provide real-time information about train schedules, seat availability, and route planning, enabling passengers to make informed decisions and avoid unnecessary waiting or delays. By engaging passengers and offering personalised experiences, rail networks can encourage ridership while maintaining energy efficiency.
  • Track and Infrastructure Maintenance: The maintenance of rail tracks and infrastructure is vital for ensuring safe and efficient operations. IoT solutions have transformed traditional maintenance practices by offering real-time monitoring and predictive analytics. Sensors embedded in tracks can detect defects, track misalignments, or stress points, alerting maintenance teams to address potential issues promptly. This proactive approach minimises the chances of disruptions, reduces the need for emergency repairs, and optimises the use of resources. By detecting and rectifying problems early, rail networks can improve safety, operational efficiency, and energy conservation.
  • Renewable Energy Integration: IoT technology facilitates the seamless integration of renewable energy sources into rail networks. Solar panels and wind turbines can be installed along rail corridors to generate clean energy. IoT-enabled sensors and smart grids efficiently manage and distribute the generated energy to power trains and stations. By reducing reliance on fossil fuel-based energy sources, rail networks can significantly reduce their carbon footprint and contribute to a greener future.

Predictive maintenance and CMMS
Predictive maintenance and Computerised Maintenance Management Systems (CMMS) play a vital role in modern, next-generation asset and maintenance management. To enhance crucial aspects such as safety, system capacity, and minimising delays, reliable railway maintenance is essential. Achieving this reliability involves the adoption of smart transportation systems and interconnected solutions, including predictive maintenance. By utilising an interconnected CMMS, it becomes possible to effectively maintain, manage, and integrate tracks, terminals, rolling stocks, and communication infrastructure.
Furthermore, it enables the identification of maintenance issues before they impact safety, operations, or revenue by collecting, storing, and analysing data. Predictive maintenance algorithms can be implemented to extend the lifespan of equipment and prevent breakdowns.

An efficient CMMS should possess user-friendly features, fast response times, and flexibility. It should also offer a mobile application for convenient access anytime, connectivity with Enterprise Resource Planning (ERP) and Internet of Things (IoT) systems, geolocation capabilities, analytical tools supporting unrestricted media uploads, and more. Additionally, it should facilitate seamless communication and connectivity among different departments such as accounting, operations, purchasing, and maintenance.

IoT in Railways

The advent of IoT has facilitated the interconnection of various objects and devices that were not a part of the network previously, and has enabled predictive analytics. In the context of trains, IoT integration offers numerous benefits in terms of safety, efficiency, and user convenience through train management systems. Control and surveillance systems equipped with IoT capabilities tends to reduce the risk of collisions and regulate the speed of the train.

Furthermore, the integration of advanced consumer technologies enhances the connectivity, allowing passengers to seamlessly continue their activities on smart devices during their journey. Cloud-based train-to-train communication enables operators to exchange data and information regarding equipments, tracks, and stations which could foster improved coordination between the train operators.

IoT also empowers remote monitoring of critical areas in railway crossings, such as barrier operations and positions, switch end positions, spacing between barriers, system operations, connections, and signals. This enables accelerated project timelines, spanning engineering, runtime, and maintenance, through swift detection and localisation of errors and faults.

By leveraging the potential of the IoT, trains become smarter and more connected, resulting in enhanced safety, efficiency, and streamlined operations throughout the railway system.

Indian Railways & Online Monitoring Rolling Stock System: New Age Technology for Predictive Maintenance

Indian Railways (IR) is embracing automation and instrumentation in its maintenance practices to detect defects and deficiencies in rolling assets. The objective is to achieve machine-assisted automatic identification of defects in the rolling stock. This shift in maintenance practices, from traditional time-based maintenance to condition-based predictive maintenance, aims to enhance the reliability, availability, and safety of the rolling stock during operations.

To accomplish this goal, Indian Railways is implementing the Online Monitoring of Rolling Stock System (OMRS). OMRS is a way-side inspection system that includes the Rail Bearing Acoustic Monitor (RailBAM) and the Wheel Impact Load Detector (WILD). These automated systems detect faults in the bearings and wheels of rolling assets, enabling the identification of defective components before they fail. This proactive approach ensures efficient utilisation of coaches, wagons, and locomotives. OMRS monitors the health of each rolling stock unit to identify any issues with bearings and wheels. Real-time defect reports are generated, and alerts are communicated to facilitate prompt corrective action.

Through the adoption of automation and instrumentation in maintenance practices, Indian Railways aims to improve the efficiency, reliability, and safety of its rolling stock, transitioning from traditional manual inspections to a more advanced and proactive approach.

To sum it up

In conclusion, the railway industry is making significant strides in integrating predictive maintenance, Big Data analytics, and Internet of Things (IoT). The emergence of advanced sensors and condition monitoring technologies enables continuous data collection and evaluation, resulting in a significant reduction in unscheduled maintenance occurrences and associated costs.

Also Read | Efficiency Upgraded: The Impact of Digitalization on Chhattisgarh Railway Corporation Limited

Notable enhancements have been observed in the form of informative and user-friendly websites, real-time mobile applications providing vehicle updates, and the implementation of e-ticketing and timetable information at stations and stops.

By harnessing the power of predictive maintenance and leveraging the insights gained from Big Data analytics, the railway industry is poised to optimise operational efficiency, enhance reliability, and deliver improved services to passengers. Embracing these advancements ensures that railway companies are well-prepared to navigate the evolving landscape and minimise disruptions in the future.

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