The Hub's vision is to use existing and develop new tailored AI tools for building lifecycle management through an Evolving Digital Twin (EDT) with sustainability as a main driver. Time is pressing for carbon emissions, which must be cut by 45% by 2030 to have a chance of meeting the ultimate target of zero emissions by 2050. The ambition of an EDT to achieve greener asset through-life management can only be tackled by joining efforts in a Research Hub, and only developed in time if accelerated by AI. The Hub will seek further long-term cross-disciplinary interaction with research groups working on ML and statistics, human behaviour within psychology and humanities and earth environment disciplines.

AI needs data. The civil engineering community has made significant progress in the production of analytical or artificial data generated by numerical simulations (e.g., Finite Element Models). Conversely, it has fallen behind in the collection of real-world quality data, most of which is still done either by error-prone and expensive human inspections or issues related to managing the pipeline, network load and data storage. However, the rapid development of sensing technologies at better prices is ameliorating this situation while presenting us at once with barriers (technical, operational and slow adoption of AI) and challenges around the following themes. Hence we need civil engineers to collaborate closely with the AI community to develop solutions.