Developing an integrative framework for digital twin applications in the building construction industry: A systematic literature review

Long, Wuyan; Bao, Zhikang; Chen, Ke; Thomas Ng, S.; Yahaya Wuni, Ibrahim

doi:10.1016/j.aei.2023.102346

Cited by 21 publications

(2 citation statements)

References 144 publications

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“…Through this publication analysis, trends in research productivity over time are tracked, revealing shifts in scholarly engagement (Ang et al, 2019). Coauthorship analysis identifies collaborative networks, key contributors, and research clusters (Donthu et al, 2020;Long et al, 2024). Country analysis highlights global research distribution and collaboration patterns (Huang et al, 2019), while keyword co-occurrence analysis reveals thematic focus and facilitates knowledge organization (Ferasso et al, 2020).…”

Section: Methodsmentioning

confidence: 99%

Utilizing intelligent technologies in construction and demolition waste management: From a systematic review to an implementation framework

Wu,

Pei,

Bao

et al. 2024

Front. Eng. Manag.

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The rapid increase in global urbanization, along with the growth of the construction industry, highlights the urgent need for effective management of construction and demolition (C&D) waste. Intelligent technologies offer a viable solution to this critical challenge. However, there remains a significant challenge in integrating these technologies into a cohesive framework. This study conducts a quantitative analysis of 214 papers from 2000 to 2023, highlighting the extensive use of artificial intelligence (AI) and building information modeling (BIM), along with geographic information systems (GIS) and big data (BD). A further qualitative analysis of 73 selected papers investigates the use of seven different intelligent technologies in the context of C&D waste management (CDWM). To overcome current limitations in knowledge, future research should concentrate on (1) the comprehensive integration of technology, (2) inclusive studies throughout all lifecycle phases of CDWM, and (3) the continued examination of new technologies, such as blockchain. Based on these insights, this study suggests a strategic framework for the effective implementation of intelligent technologies in CDWM. This framework aims to assist professionals in merging various technologies, undertaking lifecycle-wide research, and narrowing the divide between existing and new technologies. It also lays a solid foundation for future academic work to examine specific intelligent technologies, conduct comparative studies, and refine strategic decisions. Regular updates on technological developments are essential for stakeholders to consistently enhance CDWM standards.

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Section: Methodsmentioning

confidence: 99%

Utilizing intelligent technologies in construction and demolition waste management: From a systematic review to an implementation framework

Wu,

Pei,

Bao

et al. 2024

Front. Eng. Manag.

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“…In various applications, DTs are utilized during the operational phase of a building, encompassing areas such as facilities and maintenance management, monitoring, and energy simulation (Long et al, 2024). To this end, a DT can include building performance modeling programs (BPMP) to analyze and predict energy consumption, thermal comfort, indoor air quality and other aspects of building operation.…”

Section: Introductionmentioning

confidence: 99%

Optimizing office building operations: a framework for continuous dynamic energy simulations in decision-making for efficiency

Borodinecs,

Palcikovskis,

Krumins

et al. 2024

Front. Built Environ.

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Digital twins represent a promising approach for sustainable building operations and management in the context of the carbon neutrality goals of the European Union (EU). Using OpenStudio, an opensource platform for building energy modeling, we demonstrated the creation and editing of building digital twins. OpenStudio provides a user-friendly interface and extensive simulation capabilities, allowing detailed and accurate modeling of building components and systems. Using OpenStudio Measures, users can automate tasks and customize simulation models to optimize the building performance. The process of creating a building digital twin involves collecting historical data and accurately representing the building geometry; materials; schedules; and heating, ventilation, and air conditioning (HVAC) systems. Challenges such as data availability and model accuracy highlight the importance of modeling practices. Editing the digital twin involves modifying the OpenStudio model files and EnergyPlus weather files to simulate different building operation scenarios. Python programming language opportunities were considered for digital twin file modification. The potential of digital twins lies in their ability to simulate future building conditions and optimize building system settings. By integrating digital twins with machine learning algorithms and connecting them directly to building management systems, optimal building control strategies can be automated, thereby reducing energy consumption and improving occupant comfort levels.

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Conceptualizing a Digital Twin Architecture for Enhanced Control in Precast Concrete Production

Cole,

Ameri Sianaki,

Shee

2024

Lecture Notes on Data Engineering and Communications Technologies

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Developing an integrative framework for digital twin applications in the building construction industry: A systematic literature review

Cited by 21 publications

References 144 publications

Utilizing intelligent technologies in construction and demolition waste management: From a systematic review to an implementation framework

Utilizing intelligent technologies in construction and demolition waste management: From a systematic review to an implementation framework

Optimizing office building operations: a framework for continuous dynamic energy simulations in decision-making for efficiency

Conceptualizing a Digital Twin Architecture for Enhanced Control in Precast Concrete Production

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