Sustainable Digital Twins
How might we utilise data and create environmental & economic simulations for sustainable outcomes?
Description
A Sustainable Digital Twin integrates and analyses data, simulates outcomes, and is implemented in a sustainable way while focusing on sustainable outcomes.
In order to be categorised as a Sustainable Digital Twin, a user’s data must be utilised to its full potential and dealt with sustainably. Incorporating a Sustainable Digital Twin will allow effective data management to utilise or eliminate unnecessary Dark Data (data not used to derive insights or decision making, but which is still stored by an organisation or individual), reducing the cost and environmental impact of storing unused and unmanaged data.
Sustainable Digital Twins have been brought to life in: Rainforest deforestation (allowing monitoring Specialists to identify the landscapes most in need of immediate protection), Solar panel mapping (to simulate factors such as incident solar radiation, radiance values, shading and temperature) and many more.
Relevance
Digital twins are the catalyst to converging simulation, high performance computing, data analytics, and AI. For an organisation to prioritise sustainability, they must continuously review their data and identify positive changes which can be made.
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Vision
EIT Manufacturing vision for the future of Manufacturing in Europe in 2030, called ‘Fixing Our Future
Enablers
Enablers for future change and actions to make the vision, as described in Fixing Our Future, a reali
Signals
A knowledge library of over 100 signals of change, as examples of emerging manifestations towards the
About the project
Learn more about the background, the process and the people and the contributors behind this project.