Abstract
Digitalization and consistency of information about existing buildings, held by the owners, facility managers, local and national authorities, is a common issue for asset management or any other building life-cycle analysis or optimization. The digital twin concept could provide the solution; however, the creation of appropriate input data has been the main roadblock in adoption and application. The information needs for creation of digital twins of existing buildings are vast and as such none of the existing research approaches and/or algorithms are capable of holistic data collection to be used as input. A prevailing method for gathering geometrical data of existing assets is laser scanning, where a point cloud with high precision and high data volume is produced. The detection of geometrical and/or semantic information from the point cloud data has been recently a goal of many research initiatives; however they were usually focused on single purpose data extraction, thus limiting wider application. In the paper, an ontology-based approach of information creation is presented that minimizes human assistance, interaction with raw data and processing resources while increasing expressive power of the asset’s digital twin model for more efficient reasoning.
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Gregor, M., Tibaut, A. (2020). Ontology Based Information Creation Approach for Digital Twins: Early-Stage Findings. In: Borangiu, T., Trentesaux, D., Leitão, P., Giret Boggino, A., Botti, V. (eds) Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future. SOHOMA 2019. Studies in Computational Intelligence, vol 853. Springer, Cham. https://doi.org/10.1007/978-3-030-27477-1_31
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DOI: https://doi.org/10.1007/978-3-030-27477-1_31
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