In Europe, existing buildings remain at the top of energy consumption, while they are considered energy inefficient and renovated too slowly. More and more data are being generated within buildings nowadays, due to the increasing adoption of leading-edge computing technologies, contributing to moving towards a Smart Building landscape. DigiBUILD makes use of high-quality data and next generation digital building services for assuring trust, transparency and better-informed decision-making processes. This requires the use of innovative big data techniques and machine learning.

This survey aims to get your view on the utilisation of such processes and in particular artificial intelligence (AI) and digital twins (DT).

AI encompasses many types of data analysis, from machine learning (ML) to generative AI. ML is a technique used to help computers learn tasks and actions using training that is modelled on results gleaned from large data sets. DigiBUILD mostly uses ML for the large amounts of information collected from building sensors and BIMS for the purposes of improving building performance and energy efficiency. Additionally, in DigiBUILD, digital twins are used to simulate a building, its envelope and the rooms contained in the building. Sensor readings from the spaces within the buildings can also be viewed. Under DigiBUILD, a DT is also used for district heating networks.

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Share your views and help shape the future of digital building services!