Towards a digital model of the UKCS using Smart City concepts

The UK Continental Shelf (UKCS) is a complex environment with an array of varied infrastructure and interests from many different parties. This makes it difficult for stakeholders to make informed decisions that consider all of these disparate interests and their associated data streams. To help all...

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Bibliographic Details
Main Authors: Samuel R. Cauvin, Kate Gormley, Malcolm Stone, Richard D. Neilson, Marcin Kapitaniak
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Environmental Challenges
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Online Access:http://www.sciencedirect.com/science/article/pii/S2667010025001271
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Summary:The UK Continental Shelf (UKCS) is a complex environment with an array of varied infrastructure and interests from many different parties. This makes it difficult for stakeholders to make informed decisions that consider all of these disparate interests and their associated data streams. To help alleviate this we are building, as part of a suite of tools called the Smart Energy Basin, a model of the UKCS and its many datasets based on Smart City concepts. With data spread across many disparate sources, this model creates a more complete picture of the UKCS to help drive stakeholder engagement, more informed decision making, and policy development. This model comprises both 2D maps of the UKCS, and fully modelled 3D scenes of several demonstrator areas in the UKCS. A model of this type and to this extent, to the knowledge of the authors, has not been built before, and certainly not in 3D. These 3D scenes are built in the Marine Simulator at the National Decommissioning Centre, a full-physics simulator with data visualisation capabilities. As part of this we have developed automated tools for creating these 3D scenes from 2D maps, which encapsulate many datasets covering infrastructure, zoning, emissions, and marine traffic. This work is being undertaken within the Scottish Government’s Data for Net Zero (D4NZ) project, funded through its Energy Transition Fund.
ISSN:2667-0100