Signorini, M;
Moretti, N;
Merino, J;
Daniotti, B;
Parlikad, A;
(2023)
Digital-Twin based data modelling for Digital Building Logbook implementation.
In:
Low-Cost Digital Solutions for Industrial Automation (LoDiSA 2023).
(pp. pp. 130-137).
Institution of Engineering and Technology
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Abstract
Construction heavily impact on the environment, thus building management plays a central role in achieving higher sustainability objectives. In the use phase, the sustainability performance needs to be balanced with safety, health and comfort requirements, ensuring that the indoor activities can be carried out in a high-performing environment. Indoor air quality is one of the main proxies for health and safety in indoor spaces and maintaining appropriate quality levels is directly impacted by built asset condition, systems operation and other contextual factors as occupancy and weather. The Digital Building Logbook is a platform enabling the interconnection of the variety of datasets used for building management. This paper introduces a framework for implementing the Digital Building Logbook utilising semantic web technologies, in the perspective of supporting better data access and knowledge extraction for Digital Twin applications in the Facilities Management domain. The proposed framework is based on the combination of Industry Foundation Classes, the BrickSchema and a custom Digital Building Logbook ontology, needed to extend the previous two. The Digital Building Logbook ontology is based on OWL and allows to structure the information on assets, maintenance interventions associated to the different spaces and systems, while IFC and BrickSchema provide a support in representing a selection of spatial and semantic building features. The developed framework aims at enhancing the data access and knowledge extraction on the building and facilitates the digital Facilities Management applications development. A validation is carried out on the Alan Reece building at the University of Cambridge and demonstrates its effectiveness in developing users' health-based maintenance prioritisation.
| Type: | Proceedings paper |
|---|---|
| Title: | Digital-Twin based data modelling for Digital Building Logbook implementation |
| Event: | Low-Cost Digital Solutions for Industrial Automation (LoDiSA 2023) |
| ISBN-13: | 978-1-83953-932-9 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1049/icp.2023.1744 |
| Publisher version: | https://doi.org/10.1049/icp.2023.1744 |
| Language: | English |
| Additional information: | This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) |
| Keywords: | Digital twins; air quality; construction industry; structural engineering computing; semantic Web; knowledge representation languages; building management systems; production engineering computing; building information modelling; data models; maintenance engineering; facilities management; ontologies (artificial intelligence) |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10184308 |
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