A universal sensor data platform modelled for realtime asset condition surveillance and big data analytics for railway systems: Developing a “Smart Railway” mastermind for the betterment of reliability, availability, maintainbility and safety of railway systems and passenger service

Abstract

Inspired by the conventional railway systems as in signaling communications where sensing logic constitutes system fundamentals, capability of sensors or “Internet of Things (IoT)” has been exploited to improve train reliability, customer service, system maintenance and even in asset management. MTR, a world-class railway operator in Hong Kong, has been industrial leader bringing in technologies in process improvement. Chief of Operations Engineering, Ir Dr Tony Lee, has brought sensors technologies “on track” via award-winning railway applications such as monitoring train speed and position via capabilities of GPS and RFID[1], employing sensors' intelligence [2] to monitor temperature of rolling stock axle counter[3], rail integrity and even equipment rooms, sculpting the shape of future asset management of MTR with foresighted FAST 2030+ initiative (Fig. 1). Ir May Tso specializes in systems' data analysis and defining information to be captured and implanted in designing railway systems [4][5] for effective data analytics during Operations and Maintenance (O&M) cycles. These implementations provide all handy yet very effective probes to excel in managing railway engineering systems and assets that require foresightedness and vision. The Railway Mastermind is effected by the ability in consolidating centrally the railway asset condition from the track, overhead lines, rolling stock, point machines, etc. real-time so that personnel in the master chair can make efficiently effective decisions to timely or even proactively action to ensure train service reliability, availability, maintainability and safety (RAMS) which are very much crucial to the O&M of a railway system. For a railway system that has been running for decades, this systematic sensor data acquisition universal platform/model effectuates the sustainability of engineering knowledge through precise capturing of critical information that facilitates data analytics to substantiate maintenance or asset management decisions.