Mahamedi, E; Wonders, M; Kassem, M; Woo, W L and Greenwood, D (2022) Digital twin and building performance: A review and proposed framework. In: Tutesigensi, A and Neilson, C J (eds.) Proceedings of 38th Annual ARCOM Conference, 5-7 September 2022, Glasgow Caledonian University, Glasgow, UK.
Abstract
The use of Digital Twin (DT) as an emerging technology-led development encompasses data-driven methods which bring the benefit of enhancing better understanding of building performance and providing relevant information for decision making. Extensive reviews intersecting the DT concept with building performance are lacking. The aim of this paper is to present such a review and propose a framework for using DTs to develop predictive models to improve the performance of buildings. The review analyses recent studies on energy prediction performance and fault detection in building maintenance using data-driven models, and further identifies the remaining gaps in the literature. The framework incorporates artificial intelligence (AI), machine-learning (ML), and cloud computing technology in a scalable prototype solution to efficiently capture, process, and integrate real-time building data in a timely manner. The framework is expected to help decision-makers gain valuable insights into the building performance, which will then inform interventions for improving the energy efficiency.
| Item Type: | Conference Paper (Paper) |
|---|---|
| Uncontrolled Keywords: | digital twins; machine learning; artificial intelligence; building performance; predictive models. |
| Index terms: | decision-making, emerging technology, digital twin, machine learning, artificial intelligence, energy efficiency, cloud computing, building maintenance, prototype, building performance |
| Subjects: | quality assurance, digital infrastructure, decision analysis, artificial intelligence, innovation and technology management, sustainability and energy, modelling and simulation, construction type, digital engineering |
| Topics: | Engineering Principles, Risk Management, Sustainability, Construction Technology, Digital Applications, Quality Management |
| Descriptive scope: | 2 PC |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here