The first is improving asset availability, and this includes the ability to carry out “predictive maintenance” – which means making data-informed decisions about the best time to replace and repair components, ideally before they break and when the equipment would not otherwise be in use. The data is used to achieve one of three ends. Machine data on how systems are operating is also used, as are external real-time datasets such as meteorological information. Sensors on an Internet of Trains system monitor everything from engine temperature, to the open or closed state of doors, to vibrations on the rails, and even image data from outside of the trains using cameras. Of course it’s very profitable for rail operators too.” “We have seen this in Spain too – a shift away from other types of transport because trains are becoming more reliable. “This means you can rely on the train – if you have to be somewhere at 10.45am you are going to be there at 10.45am – this has made it now extremely hard to get a ticket on those trains because they are always fully booked, so now they are tendering new trains. That’s with 16 trains running multiple journeys each day. Kreß says “Since we introduced one project in Russia last year, we have had just nine delays on rail trips from Moscow to St Petersburg.
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