A Review of the Digital Twin Technology in the AEC‐FM Industry

Abstract

The Architecture, Engineering, Construction, and Facility Management (AEC-FM) industry is increasingly affected by digital technologies that monitor sensor network data and control automation systems. Advances in digital technologies like Digital Twin offer a high-level representation of buildings and their assets by integrating the physical and digital world. This paper examines patterns, gaps, and trends in the AEC-FM sector and contributes to digitalization and automation solutions for building management. This work covers a broad range of research topics, from intelligent information management of complex models to building information management and the interaction of building systems, where researchers are increasingly interested in using the Digital Twin to manage their information and in developing new research lines focused on data interchange and the interoperability of building information modeling (BIM) and facility management (FM). After a complete bibliometric search of several databases and following selection criteria, 77 academic publications about the Digital Twin application in the AEC-FM industry were labeled and clustered accordingly. This study analyzed in detail the concept of key technologies, including “Digital Twin in Facility Lifecycle Management,” “Digital Twin-Information Integration Standards,” “Digital Twin-Based Occupants Centric Building Design,” “Digital Twin-Based Predictive Maintenance,” “Semantic Digital Twin for Facility Maintenance,” and “Digital Twin-Based Human Knowledge.” The findings show that information standardization is the first major hurdle that must be overcome before the actual use of Digital Twin can be realized in the AEC-FM industry. Based on that, this paper provides a conceptual framework of Digital Twin for building management as a starting point for future research.

Recent progress and future outlook of digital twins in structural health monitoring of civil infrastructure

“…Other recent existing review papers were more inclined toward SHM-oriented DT applications. The review developed by Hosamo et al (2022) specifically focused on studies that implemented 3D laser scanning for DT applications. The studies were classified into four categories: ML, bridge management system (BMS), bridge information modeling (BrIM), and 3D modeling.…”

“…The key properties of creating a DT for BMS were highlighted, and the role of the IFC to manage and query data in a shareable file format was stressed. Hosamo et al (2022) proposed a literature review for DT applications in all of the AEC-facility management (FM) industry. Li et al (2022) discussed the implementation of advanced information technologies in phases of construction and maintenance of infrastructure.…”

Facilities Management Digitalisation Model: A Systematic Literature Review

“…By providing a real-time status of the building assets, DT technologies enable efficient and responsive planning and control of FM activities (Zhao et al, 2022). Furthermore, DT merges Artificial Intelligence (AI), Machine Learning (ML), and data analytics to create dynamic digital models that can learn and update the status of their physical counterparts from multiple sources (Hosamo et al, 2022;Wong et al, 2018;Zhang et al, 2022).…”

Digital system of engineering building modeling based on intelligent optimization algorithm

“…Xue J and Shen B (2020) proposed a new swarm optimisation method, the sparrow search algorithm, inspired by sparrow swarms in their study [5]. Digital modelling techniques can digitally process various building parameters, including but not limited to building structure, materials, and functions, to achieve integrated control and optimal design [6]. Intelligent optimisation algorithms can obtain the optimal or nearoptimal solution by optimising the building parameters to optimise the building shape and refinement design [7].…”