British railway infrastructure manager Network Rail has started trials of a new Internet of Things (IoT) predictive technology designed to prevent flooding on railway tracks as part of its TrackWater project.
Launched in October 2017, the TrackWater project also involves Lancaster University and the Transport Systems Catapult. It is funded by Innovate UK and the Department for Transport.
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TrackWater will deploy end-to-end drainage sensing and predictive modelling technology at Network Rail’s test-track in Melton Mowbray, Leicestershire. The deployment and evaluation will run until April 2019.
The predictive technology was designed by technology firm InTouch.
The trial is part of TrackWater’s focus on exploring an innovative sensor and data-driven approach to surface water management within the railway sector.
It is expected that the use of real-time information and automation will equip Network Rail with the ability to keep a tab on the rail infrastructure’s drainage system and mitigate drainage-related issues on the tracks.
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By GlobalDataInTouch managing director John Walden said: “After spending ten years successfully trialling and launching a solution to manage highways gullies, we now turn our attention to railway drainage and flooding.
“It is important that we develop our IoT technology to allow automation and data collection to be used to improve services, which can improve the lives of thousands of people using the railways.”
IoT software to assist operators in the management of flooding on tracks is also being developed.
Lancaster University research fellow Mike Harding said: “The TrackWater project is delivering leading research in collaboration with Network Rail to understand and overcome the challenges of adopting more automated, data-driven approaches to drainage management.
“Trackwater, in collaboration with transport maintenance companies, is providing a unique opportunity to better understand the real-world challenges of deploying emerging cyber-physical, data-driven technologies in a domain that traditionally has relied significantly on local knowledge to inform decision-making.
Harding added that improved monitoring of the performance of the drainage network will allow Network Rail to carry out more targeted maintenance.
