The Taiwan Railways Administration (TRA) yesterday said that it has allocated NT$68 million (US$2.32 million) to build an Internet-of-things (IoT) platform that would facilitate proactive maintenance of the railway system and enhance service punctuality.
The agency said that it decided to build the platform to promote horizontal communication among its departments after an investigation into the Puyuma Express derailment in October 2018 found that its four main departments — electrical engineering, rolling stock, construction and transportation — failed to share information with one another.
The platform would use artificial intelligence to analyze maintenance data collected by its departments, including railway crossings, tunnels, trains, railway tracks, bridges, electric cables, railway track signaling systems and other facilities, the TRA said.
Analyses of the data would help it monitor if equipment or facilities are damaged or malfunctioning and have to be maintained or replaced, it said, adding that this would help prevent service disruptions.
The platform would issue warnings for disasters and also serve as a decision support system, it said.
As crowding at certain train cars hinder passengers embarking or disembarking, which in turn affects train service punctuality, the platform would analyze train services and identify which cars have more or fewer passengers, and disclose the information at railway stations, the agency said.
This would help disperse passengers to different cars and help trains operate on time, it added.
Asked if the platform could also prevent service disruptions due to people, vehicles or foreign objects intruding on railway tracks, the agency said that it would be able to integrate data and take preventive actions in some cases, but that would be difficult if it involved foreign objects.
The agency said it plans to hire a contractor next year to build the platform between 2022 and 2023, while it focuses on gathering data.
The platform is expected to be completed by the end of 2024, it said.
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