A train operator is looking to equip as many as 40 of its trains with kit that will enable them to become ‘data hoovers’ to help transform the way the rail network is maintained.

The special trains by Northern, which would still operate public services, would travel the network and feed information about the track and surrounding infrastructure to Network Rail.

Horizon-scanning LIDAR cameras, thermal imaging software, and HD CCTV footage would all be used to record infrastructure defects, environmental factors, and maintenance issues.

Every night, the train would perform a ‘digital handshake’ so the information captured can be downloaded and analysed.

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The scheme is part of Northern’s Intelligent Trains programme, which was first announced in 2022 and is a collaboration with Network Rail designed to help make rail journeys safer, more reliable, and efficient.

Rob Warnes, strategic development director at Northern, said: “We have always sought ways to do things smarter, safer, and more efficient.

“Each of our trains travel, on average, 100,000km around the North of England every year and that presents an amazing opportunity for data capture.

“We would only need 40 of our fleet of 335 trains to be fitted with this technology to regularly sweep our entire network, which spans 3,000km of track.

“Those trains could provide engineers with data from the same section of track over many days, weeks, and months – enabling maintenance issues to be identified and repairs scheduled whilst they are within operational safety standards.”

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Northern is in talks with Network Rail to secure funding for the programme, which it estimates would save tens of thousands of ‘delay minutes’ caused by urgent, unscheduled maintenance each year.

For their work in this area, Northern has recently bee shortlisted for a 2023 Railway Innovation Award in the Engineering & Safety category. The awards, which are recognised by Modern Railways magazine in association with the Railway Industry Association, are set to take place on Friday, June 23.