Spinview, a London-based visual intelligence company that makes digital twins of physical infrastructure, has partnered with Transport for London (TfL) to digitally monitor tracks and tunnels in the London Underground.
The 3D model of London’s tube network will be used for maintenance and to provide data on noise and heat levels, as well as carbon emissions.
The initiative, funded by the government’s Smart Grant scheme, will support the Mayor of London’s ambition for a zero-carbon railway by 2030.
The project will initially focus on the Piccadilly line, a so-called “deep tube line” that reaches as far as 30m below ground.
The company’s Deep Rail Sensor (DRS) device captures the geometry of the space and “sniffs out” environmental pollutants. Those readings will establish a baseline for TfL’s current carbon emissions to help measure and track the progress of environmental goals.
Spinview’s VQecosystem and visual intelligence will provide TfL with the digital model, data, and tools that will allow the organisation to manage the Deep Tube environment in a more streamlined way.
Further, the UK company will provide TfL with a detailed and easily accessible visual recreation of its Deep Tube environment, which until now has been notoriously challenging to map in detail.
“We are thrilled to support TfL in its ambitions to achieve a zero-carbon railway by 2030,” said Linda Wade, co-founder, and CEO of Spinview. “By establishing a visually intelligent ecosystem for TfL, Spinview hopes to not only help TfL in tracking its environmental goals, but also to support in facilitating better decision-making, driving forward business efficiencies, saving costs, and future-proofing the network in the long-term.”
Paul Judge, director of the Piccadilly Line Upgrade project at TfL, said: “This partnership with Spinview offers us a really exciting opportunity to gain real-time access to our assets on the Underground network, many of which we can currently only inspect during engineering hours. Not only will using digital-twin technology support the smarter, more efficient maintenance of the railway, it will also enable us to more accurately monitor environmental challenges such as carbon emissions, noise levels, and heat as we strive to do more to lessen our carbon footprint and help tackle the climate emergency.”