E-Paper
AI innovations shaping the future for safer rail navigation
Several innovators are working on ways to reduce train accidents and make railway tracks safer for the countless people who often commute by trains
“A picture speaks a thousand words.” This age-old adage seems to have inspired a start-up that is attempting to deploy artificial intelligence and machine learning (AI & ML) into detecting anomalies in wagons with the help of pictures.
Several innovators are working on ways to reduce train accidents and make railway tracks safer for the countless people who often commute by trains. A number of such innovations that are aimed at modernising Indian Railways were on display at the sixth edition of Innorail India, an international exhibition organised here in association with Research Design and Standards Organization (RDSO).
AI identifies anomalies in wagons
Start-up ‘L2MRail’, which was incubated by Indian Institute of Science, Bangalore, has developed ‘machine vision-based inspection system (MVIS)’. S Rai Ganapa, its founder, said: “MVIS is jointly innovated by Indian Railways and IISc. It uses the power of AI and ML to automate and optimize the inspection process of rolling stocks. By using advanced image processing, our system identifies defects and other anomalies in wagons.
“It significantly enhances operational safety, reduces downtime, and minimises manual inspection errors, providing railway operators with comprehensive insights for timely maintenance and predictive analysis and provides real-time alerts by instantly generating SMS alerts on hanging parts, defective EM pads, speed, and axle count after train passage.”
He added that one of such systems was currently installed at the Aligarh railway station. “Between June 2023 to October 2024, MVIS has scanned 13,189 trains and 12,79,477 wagons or locos, and identified 21,287 defects.
Beams detect problems in wheels
Apna Technlogies & Solution has come up with two technologies to prevent train accidents: wheel impact load detector or WILD and hot box detector. These technologies were on display at the exhibition.
“WILD is an intelligent, unmanned wayside system that measures the impact load of wheels on railway tracks caused by wheel defects,” said Senthil CD, its CEO.
Vikas Gurwani, the company’s chief product officer, spoke about the beam-based hot box detector: “It is installed at the axle box level to check temperature near axle and far from axle. It is installed at the track level to measure wheel temperature. The beam can inform us about safety critical diagnostics, which can prevent catastrophes like derailment or fire on rolling stocks.”
