The SPHERE consortium aims to provide a BIM-based Digital Twin Platform to optimise the residential building lifecycle, and reduce costs and the environmental impact of the construction process. To achieve this challenging environment, SPHERE will approach these developments in layers. Each previous layer will underpin the development of the following one, so the system of systems and their tools could provide a flexible and scalable solution for the future Assets Lifecycle Management of residential stock.

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The COGITO consortium aims to materialise the digitalisation benefits for the construction industry minimising construction project time/cost overruns and alleviating workplace accidents. To do so,  COGITO targets a semantic and pragmatic alignment between novel data capture techniques and delivery of value-adding end-user services leveraging the power of near-real-time data for the timely detection of health & safety hazards to humans, construction quality defects as well as constantly up-to-date workflow management.

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The ASHVIN consortium aims at enabling the European construction industry to improve its productivity while reducing costs and ensuring safe work conditions by providing a proposal for a European wide digital twin standard, an open source digital twin platform integrating IoT and image technologies, and the standard proved to guarantee specified productivity, cost, and safety improvements.

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BIMprove has the ambition to revolutionize the European construction industry and solve long-standing problems such as decreasing productivity, dangerous environment for workers, negative environmental impact, and budget misalignment with real expenditures. To achieve these results, the project aims at developing a dynamic digital system for construction sites to fast-track productivity, cut costs and improve working conditions. The solution extends the 3D-based Building Information Modelling (BIM) systems with Digital Twin Technology,  introducing a much more dynamic and multi-functional system, reliant on real-time data.

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