The Role of BIM in Integrating Digital Twin in Building Construction: A Literature Review

Abstract

Today, construction is essential to every economy since it employs many workers and significantly contributes to GDP. The construction industry’s efficiency has lagged behind other industries for decades due to low productivity, a lack of research, and poor adoption of advancements. Fortunately, the successful development of digital technologies such as Digital Twin (DT) has facilitated growth in many sectors, and DT has the potential to address challenges in building construction projects. While DT is a virtual replica that provides real-time data and analysis of a physical asset to optimize its performance, Building Information Modeling (BIM) is a collaborative process for creating, managing, and exchanging information throughout a construction project. BIM is the most efficient way to create an accurate, high-value DT and support industry transformation. An integrated DT and BIM platform can improve building design, construction, and performance in the architecture, engineering, and construction (AEC) sectors. Based on a literature review, this research aims to clarify and differentiate DT from other advanced 3D modeling technologies, such as BIM. Related publications from articles about DT and BIM in the construction industry were selected, identified, and organized after careful research of the relevant scientific databases. The research has three primary objectives: (1) to examine the present applications of DT and BIM in the construction industry; (2) to emphasize the similarities and differences between the two; and (3) to develop solutions and design methods for BIM and DT integration in building construction.

1. Introduction

The construction industry faces the challenge of integrating the digital and physical worlds. There is a lack of connection between data analysis and the corresponding action, resulting in information fragmentation, data duplication, and inefficiency throughout the construction life cycle [1]. This disconnection reduces management efficiency and causes delays in collaboration among construction stakeholders. Construction sites are dynamic, with frequent changes in facilities, equipment, materials, people, design, and several other components at different phases, increasing the need for coordination and collaboration [2]. The DT can provide effective solutions to address these problems.

Some of the research literature discusses DT implementation, focusing on the AEC sector. According to [3], DT has three key elements: physical items in real life, virtual products in the virtual world, and the connectivity of data collecting and information that links them together. Integrating its data in real and virtual representations helps optimize the performance of the real assets [4]. Many authors use the term of “Digital twin” technology merely as a synonym for Building Information Modeling (BIM) models generated during design and construction in various built environment studies [5]. Autodesk [6] stated that the BIM process combines data created during the planning and design phases. While DT extends data capture to the asset’s construction and operational phases, it could predict future projects [6]. From the construction perspective of [7], BIM is a set of processes, applications, and data formats that allow a consistent, semantic representation of building parts and systems. For a DT to succeed, it is crucial to incorporate models encompassing multiple disciplines and connect systems and data throughout workflows and organizations [6]. Accordingly, BIM is the most efficient path to creating an accurate, high-value DT [6]. As stated by Boje et al. [7], to embrace more integrated approaches at both the micro (construction site) and macro (city district) levels, it is necessary for BIM to adopt the DT paradigm. It would help deliver more innovative construction services, increase automation, and information consistency.

As a result, both the academic community and the construction industry have been actively involved in researching, developing, and applying DT or its underlying principles. This review aims to address the following research questions (RQs):

RQ1:

What is the available research on Digital Twin with BIM?

RQ2:

How did Digital Twin evolve from BIM?

RQ3:

What are the current studies to compare Digital Twin with BIM?

RQ4:

How can BIM advance DT in building construction?

The paper is organized into the following sections: After the introduction, it presents the background of DT and BIM in the building construction context. The next section relates to data analysis and explores the research conducted on DT, BIM, and the comparison of DT and BIM. Section 3 defines the methodology used for the study and discusses the limitations of the research. Section 4 is a literature review describing DT and BIM’s current uses in the construction industry. Section 5, the results and discussion, proposes solutions and design methods for integrating BIM and DT in building construction. The two last sections are the conclusions and the list of references.

2. Background

2.1. Concept of BIM

Firstly, BIM took remarkably long to displace its predecessor, initially starting with hand-drafting, computer drafting, computer-aided design (CAD), and other computer-based systems. The construction process is information intensive, and throughout the project life cycle, a vast amount of information is exchanged and shared [1]. Rework, inefficiency, data loss, and falsification are all consequences of the old paper-based information management system [8]. BIM can address these issues by encompassing the entire project process from initiation to completion, facilitating a cohesive and transparent flow of models throughout the life cycle [1]. It helps improve the construction process’s efficiency and accuracy [1]. Moreover, it is technically designed to increase information integration among project stakeholders significantly. Integrated information is the foundation and the source of integrity and insight, which allows an integrated team to make the best decisions for the project [9]. By using visualization as a platform, BIM can help an integrated team create the aesthetics of a design and interpret the values of the building’s owner and end users. Simulation is another major use of BIM, which allows teams to evaluate alternative designs and strategic interventions to reduce risks and negative impacts. In addition to monitoring the initial cost, the team can now analyze energy consumption, workflow, natural light, and previously unmeasurable values, such as openness, connectedness, etc. [9].

BIM has been around since the early days. Prior to BIM, pioneering scholars, including Chuck Eastman, used the term Building Description System. Moreover, like DT, BIM gained popularity in the early 2000s thanks to companies such as Autodesk, Bentley Systems, and others. The initial purpose of BIM research remains the same today as it did in the beginning. The inventors of BIM anticipated that such a system would be useful for contractors in large projects, providing both a visual and quantitative representation of the construction [10]. They argued that it would also assist in material procurement and project scheduling. The initial concept of BIM has proven to be accurate. Furthermore, well-known BIM software companies attract AEC professionals by highlighting the cost-saving advantages of having a centralized reference point for building information in a 3D digital model. Since then, BIM has become prominent, containing geometric and semantic information about building elements [10]. BIM allows AEC professionals to collaborate seamlessly across different lifecycle stages, including the design, construction, and operating phases [11]. With the development of BIM platforms, construction processes and workflows have grown considerably [12]. The availability of a digital prototype enables the testing of design and production aspects prior to the actual construction phase. Although BIM appears comprehensive like DT, significant differences are mentioned in the following sections of this research.

2.2. Concept of Digital Twin

In recent years, BIM has developed alongside the DT concept. The Building Digital Twin Association defined DT as a digital representation of a physical manufacturing system that may run several simulation disciplines and is synchronized bi-directionally with feedback loops utilizing sensed data and linked smart devices [13]. The goal of this concept is to connect the physical world with a digital platform in order to efficiently manage and oversee the construction process, facility management, environmental monitoring, and other life cycle processes related to the built environment [12]. The progress of the DT is driven by advancements in related technologies and initiatives such as the Internet of Things (IoT), Big Data, multi-physical simulation, Industry 4.0, Real time sensors and Wireless Sensor Networks (WSN), data management and processing, and future prospects of digital manufacturing [14]. In 2002, Dr. Michael Grieves presented a paper at the Product Lifecycle Management Special Meeting that formally debuted the initial concept of DT. The Information Mirroring Model was later used to characterize the idea after it was first articulated as the Mirrored Spaces Model [15,16]. Until recently, these expressions were all referred to as Digital Twin [17]. The DT concept provides scholars and academic researchers with numerous new perspectives and future research directions. This research on integrating BIM and DT in design construction could answer how innovative technologies, particularly BIM and DT, can help maintain sustainability.

DT technology creates a virtual space where production activities can be simulated and predicted alongside the physical world, maximizing the value of information and saving physical resources. DT enables designers to fully utilize their creativity in optimizing the structural design, while organizational managers can adopt more effective management techniques to enhance the integration of social resources. Ultimately, DT will facilitate the improvement and modernization of industrial structures as well as the digitalization of the construction industry [18].

2.3. Advancement of BIM to Digital Twin

BIM is a technique that involves creating and managing a digital model that contains detailed information about a particular asset. This process relies on the collaborative gathering and updating of information at crucial stages of the project, which reduces the likelihood of disagreements between various parties involved. BIM has played a crucial role in enabling the integration of DT technology, which essentially produces a virtual duplicate of physical assets and provides instantaneous information and analytical insights. This technology has progressed significantly across areas of technology, process, and policy, but significant changes in workflow and project delivery processes are required to leverage BIM’s benefits entirely [19].

Using Wireless Sensor Networks (WSN) in conjunction with BIM has created an active model that enables real-time monitoring and analysis, effectively implementing DT technology in the construction field. During the design phase, DT is advantageous as it offers designers efficient information, empowering them to make well-informed decisions. Additionally, the information acquired through DT can be stored in a database and accessed by designers for future projects, aiding them in making better decisions related to material selection, energy management, procurement, supplier selection, and other aspects [19].

BIM and Common Data Environment (CDE) are heavily relied on during the upstream parts of the life cycle. The focus is digitally storing as-designed, as-planned, and as-built data and information. According to Seaton et al. [18], DT takes BIM and CDE beyond this static representation by considering how built assets behave and perform over time with respect to past recreations, real time, or future projections. BIM provides an efficient mechanism for creating an accurate and high-value virtual representation and a foundation for the information management framework for the data and information. DT and BIM are predicted to effectively merge into one set of systems in the future [18].

Organizations with greater BIM adoption and process development are in a better position to use DT. BIM is considered the best tool for creating static data for construction objects, specifications, schedules, and design and construction documentation. BIM is becoming a vital part of DT initiatives. When stakeholders use BIM for communication and collaboration, it fosters trust and empathy among them, ultimately reducing disputes. Thanks to BIM models, conflicts among project stakeholders have significantly decreased. Designers can use BIM to make early design decisions that serve as pre-construction guides [18].

Utilizing DT and BIM presents fresh prospects for integrating design and construction and digitally upgrading the construction sector [20]. The combination of BIM and DT enables seamless collaboration between various teams involved in a built asset’s design, construction, and operation. These technologies have the potential to bring new insights and improve decision-making abilities at every stage of the built environment’s life cycle. Although research into digital technologies for the built environment is still relatively new, it is critical to comprehend the advancements in the underlying enabling technologies and create a shared framework for continued and future research [11].

3. Methodology

The analysis methodology used for this study was a qualitative method (concepts and experiences). This study provides a set of data analyses to present the qualitative approach through concepts, experiences, and insight into scholarly publications.

At first, the data collection was retrieved from multiple resources, including Google Scholar, Scopus, Web of Science, etc. To expand our knowledge on the topic, we began our research by using Digital Twin (DT) along with BIM and Building Construction as search keywords to identify innovative approaches for this study.

Second, the initial literature review identifies research gaps and emerging trends in relevant topics. The initial stage of research involves exploring relevant keywords to gain a comprehensive understanding of the existing knowledge and the limits and parameters of the chosen field. Most of these studies were published in popular journals regarding construction technologies. When conducting research, a thorough analysis of 150 studies is undertaken. The authors then focused on the 30 research studies that examine the BIM and DT concept in the industry. This process allows for a deeper understanding of the existing knowledge and limitations of the selected field of study. Additional studies from different resources and databases within the same research fields were also included: Engineering, Computer Science, Energy, Environment Science, and Multidisciplinary.

Third, based on an initial literature review of papers, the study selected and focused on 30 academic papers on DT and BIM in the construction industry. The reviewed literature has enabled us to present and summarize the current state of DT and BIM in construction industry, such as how DT gains attention in construction industry, requiring BIM, data integration, advanced technologies, and interdisciplinary collaboration for real-time decision-making, efficiency, and security. In conducting the detailed literature review, this research attempts to answer the following research questions regarding the concept of DT, the concept of BIM, the current connection, and the comparison of DT and BIM in building construction. The study has provided criteria for comparison to highlight the practical distinctions between the two concepts. By exploring and discussing these criteria, the authors aim to provide insights and guidance to practitioners and researchers in the field. The intention behind this comparison is to foster a better understanding of each approach’s strengths and limitations and facilitate their effective utilization in building construction.

4. Literature Review

We have conducted a thorough examination of recent publications on DT and BIM, resulting in a comprehensive literature review of 30 papers which can be found in

Table 1. List of journals and articles related to a detailed literature review.

#	Authors/Years		Journals/ Conferences	Methods	Broad Area
1	Khajavi et al. (2019)	[21]	IEEE	Experimentation Testing	Construction
2	Boje et al. (2020)	[7]	Automation in Construction	Literature Review	Construction
3	Jones et al. (2020)	[22]	CIRP-JMST	Literature Review	Multidisciplinary
4	Sacks et al. (2020)	[5]	Data-Centric Engineering	Literature Review	Construction
5	Sepasgozar (2021)	[23]	MDPI	Literature Review	Construction
6	El Jazzar et al. (2020)	[24]	Conference Paper	Literature Review	Construction
7	Shahzad et al. (2022)	[25]	MDPI	Literature Review Interviews	Multidisciplinary
8	Alonso et al. (2019)	[26]	MDPI	Literature Review	Construction
9	Deng et al. (2021)	[11]	IT Con	Literature Review	Civil Engineering
10	Opoku et al. (2021)	[27]	Building Engineering	Systematic Review	Construction
11	Lu et al. (2020)	[2]	CSIC	Literature Review	Construction
12	Zhang et al. (2022)	[1]	ASCE	Questionnaires Interviews	Construction
13	Sawhney et al. (2020)	[28]	ASC	Literature Review	Construction
14	Madubuike et al. (2022)	[29]	IT Con	Systematic Review	Construction
15	Feng et al. (2021)	[30]	ISARC	Literature Review	Construction
16	Zhou et al. (2021)	[20]	PSGEC	Literature Review	Construction
17	Zhang et al. (2021)	[31]	Tech. Science Press	Literature Review	Construction
18	Akanmu et al. (2021)	[12]	IT Con	Literature Review	Construction
19	Grieves (2019)	[32]	Astronautics Aeronautics	Literature Review	Engineering
20	Seaton et al. (2022)	[18]	World Built Environment Forum	Literature Review Case Studies	Construction
21	Zhang et al. (2021)	[33]	Frontiers in Sustainable Cities	Literature Review	Construction
22	Hosamo et al. (2022)	[34]	Hindawi Civil Engineering	Literature Review	Construction
23	Douglas et al. (2021)	[35]	Computing in Construction	Systematic Review	Construction
24	Gorse et al. (2020)	[36]	SEEDS	Literature Review Interviews	Construction
25	Sobhkhiz and El-Diraby (2022)	[37]	ASCE	Case Study	Construction
26	Almatared et al. (2022)	[38]	ASCE	Literature Review	Construction
27	Quirk et al. (2020)	[39]	ASHRAE	Literature Review	Construction
28	Bolpagni et al. (2021)	[40]	Structural Integrity 20	Case Study Literature Review	Construction
29	Daniotti et al. (2022)	[41]	MDPI	Literature Review Experimentation Testing	Construction
30	Baghalzadeh et al. (2022)	[42]	MDPI	Literature Review	Construction

Note: Table A1 in the Appendix A (Summary Table of Selected Topics) provides more information to enhance the organization and readability of research papers and delivers the essential findings and methodological aspects of the reviewed articles.

. The literature review was not meant to cover all the DT-related work in the construction industry, as it was not an exhaustive review. Additionally, it mainly focused on articles published between 2019 and 2022 to provide the latest information on DT.

Table A1. Summary table of selected topics.

#	Titles	Authors/ Years	Citation #	Journals/ Conferences	Research Methodologies	Key Findings
1	Digital Twin: Vision, Benefits, Boundaries, and Creation for Buildings	Khajavi et al. (2019)	[21]	IEEE	Experimentation: Testing—Sensor network used to create DT of a building.	Proposing a framework to enable a DT of a building facade.
2	Towards a semantic Construction Digital Twin: Directions for future research	Boje et al. (2020)	[7]	Automation in Construction	Literature Review: The research approach is divided into three steps: reviewing BIM, analyzing DT uses, and identifying research gaps.	BIM can be used to create a construction DT concept, allowing for more efficient construction.
3	Characterizing the Digital Twin: A systematic literature review	Jones et al. (2020)	[22]	CIRP-JMST	Literature Review: This paper provided a characterization of the DT, identified gaps in knowledge, and identified areas for future research.	Identifying 13 characteristics of the DT and its process of operation, as well as 7 knowledge gaps and topics for future research focus.
4	Construction with digital twin information systems	Sacks et al. (2020)	[5]	Data-Centric Engineering	Conceptual analysis: Analyzes construction project management processes, digital tools, and workflow frameworks.	Four core information and control concepts for DT construction, focusing on concentric control workflow cycles and prioritizing closure.
5	Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment	Sepasgozar (2021)	[23]	MDPI	Literature Review: This section analyzes DT scientific research quantitatively, using scientometric analysis to identify trends, challenges, and publications in various fields.	DT applications are recommended for real-time decision-making, self-operation, and remote supervision in smart cities, engineering and construction sectors post-COVID-19.
6	Digital Twin in construction: An Empirical Analysis	El Jazzar et al. (2020)	[24]	Conference Paper	Literature Review DT practice in construction: Categorizes integration into Digital Model, Digital Shadow, and DT.	Developing the framework for understanding DT implementation in the construction industry.
7	Digital Twins in Built Environments: An Investigation of the Characteristics, Applications, and Challenges	Shahzad et al. (2022)	[25]	MDPI	Literature Review: Semi-structured interviews with ten industry experts.	Exploring the relationship between DTs, technologies, and implementation challenges.
8	SPHERE: BIM Digital Twin Platform	Alonso et al. (2019)	[26]	MDPI	Literature Review: Collaborative practices are facilitated using the IDDS framework and PAAS platform for data integration and processing.	SPHERE platform improves building energy performance, reduces costs, and enhances the indoor environment.
9	From BIM to Digital Twins: A Systematic Review of the Evolution of Intelligent Building Representations in the AEC-FM industry	Deng et al. (2021)	[11]	IT Con	Literature Review: Review of emerging technologies for BIM and DTs.	Developing a five-level ladder categorization system for reviewing studies on DT applications, focusing on the building life cycle, research domains, and technologies.
10	Digital twin application in the construction industry: A literature review	Opoku et al. (2021)	[27]	Building Engineering	Systematic Review: The study analyzes DT concepts, technologies, and applications in construction using systematic review methodology and the science mapping method.	Highlighting six DT applications in construction, highlighting their development in various lifecycle phases but focusing on design and engineering over demolition and recovery.
11	From BIM towards Digital Twin: Strategy and Future Development for Smart Asset Management	Lu et al. (2020)	[2]	CSIC	Literature Review: The study reviews latest research and industry standards impacting BIM and asset management.	Proposing a framework for smart asset management using DT technology and promoting smart DT-enabled asset management adoption.
12	Digital Twins for Construction Sites: Concepts, LoD Definition, and Applications	Zhang et al. (2022)	[1]	ASCE	Questionnaires and interviews are used to propose a framework that enhances construction site monitoring, management, quality, efficiency, and safety.	Proposing a framework for utilizing DTs to extend BIM, IoT, data storage, integration, analytics, and physical environment interaction in construction site management.
13	A Proposed Framework for Construction 4.0 Based on a Review of Literature	Sawhney et al. (2020)	[28]	ASC	Literature Review: The study reviews Industry 4.0’s impact on the construction sector, defining the framework, benefits, and barriers.	Revealing BIM and CDE are crucial for Construction 4.0 implementation, transforming the industry into efficient, quality-centered, and safe.
14	A Review of Digital Twin Applications in Construction	Madubuike et al. (2022)	[29]	IT Con	Systematic Review: The study reviews literature, analyzes existing and emerging applications, and identifies limitations.	Evaluating DT technology’s benefits in construction, comparing applications, and identifying limitations.
15	Application of Digital Twin Technologies in Construction: An Overview of Opportunities and Challenges	Feng et al. (2021)	[30]	ISARC	Literature Review: 23 recent publications were reviewed for DT development in construction.	DT technologies in the AEC industry face challenges in data integration, security, and funding, requiring skilled professionals and advanced technologies.
16	Design and Construction Integration Technology Based on Digital Twin	Zhou et al. (2021)	[20]	PSGEC	Literature Review: Review recent papers on the application of DT in substation design and construction integration.	Improving performance, reducing construction difficulties, and simplifying maintenance by addressing low digitization intelligence issues.
17	Digital Twin-Driven Intelligent Construction: Features and Trends	Zhang et al. (2021)	[31]	Tech. Science Press	Literature Review: The study reviews DT-driven IC usage, focusing on information perception, data mining, state assessment, and intelligent optimization.	Sustainable IC and DT enhance construction industry efficiency, real-time structure monitoring, and safety prediction, with four aspects proposed for digital dual-drive sustainable intelligent construction.
18	Towards Next Generation Cyber-Physical Systems and Digital Twins for Construction	Akanmu et al. (2021)	[12]	IT Con	Literature Review: The paper reviews evolution, applications, limitations, next generation CPS/DTs, enabling technologies, and conclusions in construction.	Exploring opportunities for CPS and DT in construction, promoting increased deployment and workforce productivity.
19	Virtually Intelligent Product Systems: Digital and Physical Twins	Grieves (2019)	[32]	Astronautics Aeronautics	Literature Review: Paper explores interconnected Physical Twin, product lifecycle, and DT concepts.	DT concept requires value-driven use cases, with new ones emerging as technology advances.
20	Digital twins from design to handover of constructed assets	Seaton et al. (2022)	[18]	World Built Environment Forum	Literature Review; Case Studies; Interviews: The paper examines DTs’ dimensions, application, asset life cycle, and use cases from the perspective of professionals in the built environment sector.	DTs in the built environment require accurate definition, efficient data management, and high BIM adoption for success.
21	Digital Twin for Accelerating Sustainability in Positive Energy District: A Review of Simulation Tools and Applications	Zhang et al. (2021)	[33]	Frontiers in Sustainable Cities	Literature Review: Review of DT for PEDs, discussing concepts, principles, tools, and applications.	Digital PED twin consists of virtual models, sensor network integration, data analytics, and a stakeholder layer, with limited tools for full functionality.
22	A Review of the Digital Twin Technology in the AEC-FM Industry	Hosamo et al. (2022)	[34]	Hindawi Civil Engineering	Literature Review: 77 academic publications clustered around DT applications in the AEC-FM industry.	DT implementation in the AEC-FM industry requires information standardization and a conceptual framework.
23	BIM, Digital Twin and Cyber Physical Systems: Crossing and Blurring Boundaries	Douglas et al. (2021)	[35]	Computing in Construction	Systematic Review: The paper reviews DT BIM and CPS concepts, promoting discussion in construction.	Identifying three distinct DT and BIM understandings, requiring further investigation.
24	Climate Emergency—Managing, Building, and Delivering the Sustainable Development Goals	Gorse et al. (2020)	[36]	SEEDS	Literature Review; Interview; Case Studies: Data collection, communication, and rapid response processes.	Proposing the growth of DT as benefits realized over time and an approach to DT for BIM-enabled asset management.
25	Developing BIM-Based Linked Data Digital Twin Architecture to Address a Key Missing Factor: Occupants	Sobhkhiz and El-Diraby (2022)	[37]	ASCE	Case Study: Extended the DT architecture for addressing issues.	Proposing architecture for designing DTs using semantic web technologies, linked data approaches, machine learning, and BIM integration.
26	Digital Twin in the Architecture, Engineering, and Construction Industry: A Bibliometric Review	Almatared et al. (2022)	[38]	ASCE	Literature Review: Research synthesizes DT in the AEC industry using bibliometric analysis, identifying trends, challenges, and knowledge gaps.	Exposing quantitative research trends and needs for DT in the AEC industry. Future research should focus on data interoperability, AIoT, and AI.
27	Digital Twins: Details Of Implementation	Quirk et al. (2020)	[39]	ASHRAE	Literature Review: This article discusses implementing a DT, validating results, and real-time calibration.	DTs enable ongoing monitoring of data center environments, enabling rapid decision-making and energy efficiency optimization, reducing surprises, and enhancing business efficiency.
28	Industry 4.0 for the Built Environment: The Role of Digital Twins and Their Application for the Built Environment	Bolpagni et al. (2021)	[40]	Structural Integrity 20	Case Study: Literature Review of DT vision, utilization, BIM specifications, and energy efficiency management in facility management.	Discussing DT concept, human–building interaction, post-construction use cases, property management, field data, and practical solutions.
29	The Development of a BIM-Based Interoperable Toolkit for Efficient Renovation in Buildings: From BIM to Digital Twin	Daniotti et al. (2022)	[41]	MDPI	Literature Review: A European project validates the BIM4EEB renovation toolset using KPIs in real-world cases.	Developing the Horizon2020 Project’s BIM-based toolkit development, real-world validation, and benefits enhance the building renovation process.
30	Internet of Things (IoT), Building Information Modeling (BIM), and Digital Twin (DT) in Construction Industry: A Review, Bibliometric, and Network Analysis	Baghalzadeh et al. (2022)	[42]	MDPI	Literature Review: Reviews 1879 studies in Web of Science database network on visualization, research interactions, and influential authors.	Revealing prolific authors, prominent journals, nations, popular topics, and future trends.

Note: LoDs: level of details; CPS: cyber-physical systems; PED: positive energy districts; AIoT: Artificial Intelligence of things; SPHERE: Service Platform to Host and share Residential data; IDDS: Integrated Design and Delivery Solutions; PAAS: Platform as a Service; BIM4EEB: BIM-based fast toolkit for the efficient renovation of residential buildings; KPIs: key performance indicators.

in the Appendix A presents a summary of 30 selected papers on BIM and DT in the construction industry. These papers employ various research methodologies, including literature reviews, case studies, interviews, questionnaires, conceptual analysis, and experimentation. The key findings highlight the potential benefits and challenges of DT implementation, the relationship between BIM and DT, and the applications of DT in construction. Common themes include the need for data integration, information standardization, and advanced technologies to support DT implementation. Several papers focus on literature reviews, providing a comprehensive overview of existing knowledge and identifying research gaps. These include papers by Jones et al. [22], El Jazzar et al. [24], Opoku et al. [27], Shahzad et al. [25], and others. Some papers utilize case studies and interviews to investigate the practical implementation of DTs in specific contexts. Examples include papers by Seaton et al. [18], Sobhkhiz and El-Diraby [37], and Bolpagni et al. [40]. Certain papers propose frameworks or methodologies for DT implementation in construction. For instance, papers by Sacks et al. [5], Zhang et al. [1], and Lu et al. [2] present frameworks to enhance construction project management, site monitoring, and asset management, respectively. A few papers employ experimentation or empirical analysis to explore DT-related concepts and practices. Notable examples include papers by Deng et al. [11] and Almatared et al. [38]. These authors provide insights into the applications of DT across various construction lifecycle phases and emphasize the importance of BIM as an underlying technology.

Over the past few years, there has been a notable increase in interest in implementing DT technology in the construction sector due to its potential to enhance building performance, reduce costs, and improve communication and collaboration among stakeholders. To investigate the state of the art in construction field, Deng et al. [11] performed a comprehensive analysis of the available literature to discover and pick out relevant articles that were released in bibliographic databases. Deng et al. [11] aimed to answer three research questions and employed a five-level ladder taxonomy to reflect the evolution from BIM to DT. The authors used Google Scholar, Scopus, and Science Direct as search engines and collected articles post-2010 related to “BIM”, “IoT”, and “Digital Twin” associated with “building”. The researchers could manually filter and select relevant articles from bibliographic databases by examining the literature. The chosen papers were limited to English documents published in journal papers and conference proceedings. The authors identified 23 BIM review papers and 100 original papers, which were classified into five levels of the ladder taxonomy below to answer research questions.

Deng et al. [11] conducted a comprehensive literature review on DT and used a five-level ladder taxonomy to classify relevant studies, as shown in Figure 1. Their research presents a synopsis of the present status of DT technology, bringing to light the development from BIM to the completed DT. The study also provides insights into the subcategories of research areas at each taxonomy level, which can guide future research and development of DT in the construction industry. The ladder classification was segregated into different subcategories to answer research questions about the life cycle of buildings and the number of relevant papers. For example, Level 1 has subcategories such as BIM-based design and construction management. In contrast, Level 2 has subcategories such as BIM-based energy simulation and occupant behavior simulation. The study delivered a comprehensive analysis of the present status of DT and demonstrated the progression from BIM to ideal DT. Additionally, it offers insights into the subcategories of research areas at each taxonomy level, which can help guide future research and development of DT in the construction industry.

Implementing BIM in the construction industry has been slow due to perceived risks and challenges, resulting in a lack of knowledge and understanding of the technology and causing abandonment. Still, DT technology has the potential to impact various technologies used in the industry, including BIM, by ensuring iterative optimization of both models, reducing the overall design process, and minimizing additional costs during rework. DT application in the construction industry has mainly been focused on BIM during a construction project’s design and engineering stage. While BIM and DT share some similarities, they differ in purpose, technological aspects, users, and facility life stage [27]. DT provides a dynamic and responsive model that supports various decisions at different project lifecycle phases, while BIM works with static, non-real time data.

The low digitization intelligence problem in the current design and construction integration process can be effectively resolved using DT technology. According to a study by Zhou et al. [20], DT technology has successfully integrated architectural design and construction. This technology creates a virtual space mapping model that reflects a physical system’s entire life cycle process by incorporating historical operation data and sensor data updates. DT can simulate the entire life cycle during the design stage and provide feedback to help designers make informed decisions regarding building performance under different parameters. DT can identify and address any issues during construction, leading to better quality and reduced difficulty. In the operation and maintenance stages, DT can collect more data to diagnose and analyze the building’s internal state accurately, simplifying maintenance and making it more efficient.

The construction industry is experiencing notable transformations by embracing BIM and DT technologies. Although BIM has faced reluctance in its adoption worldwide due to concerns and obstacles, DT can revolutionize most of the technologies utilized in the sector. The application of DT in integrating architectural design and construction can provide significant benefits, including reflecting the whole lifecycle process, providing feedback to designers, and analyzing internal building data to improve maintenance.

4.1. Discussion on Available Research on Digital Twin with BIM

Figure 2 showcases a compilation of the most frequently used terms obtained by gathering various explanations found in the literature. The prominent terms that emerge from the word cloud are “Digital”, “Twin”, “BIM”, “Data”, and “Construction”, reflecting the consensus among both academic research and the construction industry regarding the key elements of these concepts. The word cloud visually represents the frequency and importance of these terms in relation to DT and BIM. By conducting data mining, we found essential keywords, and one that stands out is “Data”. The inclusion of “Data” as an essential keyword underscores the role it plays in enabling effective integration, as data serve as the foundation for generating accurate digital representations and facilitating information exchange throughout the construction process. Based on some literature reviews, BIM is suitable for managing data across the building construction sector, but it has limitations such as authorship issues, liability, traceability, and transparency issues [36,40]. Jones et al. [22] and Zhang et al. [1] also suggested these types of issues in their studies. How, then, can we solve this data issue? We conducted another literature review about DT and DT–BIM, data traceability, and data transparency. By combining these tools, we may propose a new framework for data management in design, construction, and performance in building construction. Data and information management are vital drivers of DT’s development, deployment, and use in the built environment sector. DT relies on a repository of static and dynamic data of real-world entities and processes. Thus, the success of a DT application depends on information management processes adopted by the implementation team. DT meets the client’s information requirements and makes the right decisions to maintain sustainability [18].

There is a growing body of research on using DT and BIM in the construction and engineering industries. Researchers have been exploring various aspects of this technology, including:

• Integration of BIM and DT: Douglas et al. [35] focused on using real time data from sensors and other sources to enhance the DT, as well as using data analytics and machine learning algorithms to analyze these data and make predictions about building performance;
• Real time data analysis: Opoku et al. [27] and Deng et al. [11] focused on using real time data from sensors and other sources to enhance the DT, as well as using data analytics and machine learning algorithms to analyze these data and make predictions about building performance;
• Simulation and visualization: there has been research on using simulation and visualization technologies to enhance the DT and improve decision-making in the construction and engineering industries [21,27];
• Cost and resource optimization: DT and BIM potentially reduce costs, improve resource allocation, and increase overall efficiency in the building construction process [33,40];
• BIM/DT in the context of sustainability: the integration of BIM and DT support sustainable design and construction practices by incorporating data on energy efficiency [21], material usage [26], and environmental impact [18]; it integrates real-time data from sensors and IoT devices [21], enabling continuous monitoring [5], analysis, and proactive maintenance [34] for sustainable practices.

DT has received rapidly growing interest in the construction sector in recent years. DT technology has seen extensive deployment across various industries, leading to the development of diverse conceptual models and system architectures [29]. However, the construction industry’s efforts toward developing DT models are still in their infancy [5]. The academic community has made valuable contributions in leveraging digital technologies and BIM in the past few years, resulting in the formulation of conceptual frameworks for DT [5].

El Jazzar et al. [24] found that in many papers, the term “Digital Twin” is not explicitly mentioned and is instead referred to as BIM or BIM-FM. Despite being extensively applied in the design and construction stages, the utilization of BIM in the operation and maintenance phase is restricted [2]. The fundamental structure of DT is based on BIM technology, which is a digital representation of the facility. The capabilities of DT technology include constant monitoring, updating in real time, simulating scenarios, analyzing data, controlling operations, predicting outcomes, and optimizing performance [43,44]. It also includes IoT, which contains sensor technology, data storage, integration, and analytics [1]. DT interacts with the physical environment to collect data during the operation and maintenance. Architects can save these data in a database and use them for future projects [45]. DT also includes BIM and 3D models, 2D models, schedules, contracts, construction documents, operational data collected by embedded sensors, artificial intelligence (AI), and machine learning technology data regarding design and the built environment [29].

DT has been quickly adopted in construction engineering, with BIM-centered technology serving as the mainstay technology for DT [31]. Akanmu et al. [12] also emphasized that BIM should be extended to realize the potential of DT fully. Despite the various applications of DT technology in construction, there is a significant gap in the research on utilizing DT for managing the entire construction site process, as well as its prominent implementation on construction sites [1]. Therefore, DT is an essential tool that can help optimize building design and improve operational efficiency. DT technology should be explored further in the construction industry to improve building design, construction, and operation and address research gaps.

4.2. Evolution of Digital Twin from BIM

This part highlights the evolution of BIM, the concept of a DT, and how these technologies can potentially transform the construction sector. The fundamental concept of incorporating DT technologies in the industrial sector involves the utilization of BIM-based platforms and cooperative models to enhance construction and design techniques [29]. The industry has made significant progress in technological advancements and applications, especially in improving information management through BIM [24]. It has transformed the traditional paradigm of the construction industry from 2D-based drawing information systems to 3D-object-based information systems. BIM has developed an innovative approach towards building design holistically. It has enhanced communication and collaboration among key stakeholders, increased productivity, improved the final product’s overall quality, reduce the construction industry’s fragmentation, and improve its efficiency [21]. One of the most significant benefits of BIM is its ability to represent accessible information throughout a project lifecycle rather than being fragmented [46]. Despite its usefulness, BIM is limited in its ability to provide dynamic information about the built environment. It cannot automatically update real time data in its models without the help of external sources [11]. This is where the IoT comes into play. The IoT refers to the interconnection of various sensing devices that can exchange information across different platforms [47]. With the introduction of IoT, it has become feasible to combine real time sensory information with the fixed data supplied by BIM models [48]. By skillfully merging BIM and IoT technologies, it is possible to keep an eye on the construction process and the indoor environment of buildings in real time [49]. This integration of BIM and IoT has given rise to DT, which has the potential to solve many construction-related issues [2].

Figure 3 illustrates how DT is employed in construction. To fully realize the potential of DT, it is crucial to initiate it at the early stages of the project and maintain it throughout the facility’s lifecycle. For instance, during the design phase, the data collection process should begin using a BIM model [21]. This model should be continuously updated and gathered throughout the construction project lifecycle to provide a comprehensive as-built model for the commissioning phase. During the operation and maintenance phase, the model collects data from various sensors, such as pressure and heat, which are then analyzed using cloud-computing techniques such as data mining and big data [21]. The virtual representation is then updated in real time with the relevant data and predictions of the physical facility’s behavior. This feature enables the facility owner, manager, and operator to make informed decisions, and the bidirectional communication between the physical and virtual facility allows proactive maintenance [21]. Additionally, applying this concept, in the long run, can improve future construction projects by utilizing the knowledge captured in DT. Advancements in technologies such as IoT, Big Data, multi-physical simulation, Industry 4.0, real-time sensors, wireless sensor networks, data management and processing, and digital manufacturing prospects are driving the progress of DT. As shown in the figure, establishing a DT for a building involves several essential elements. The figure highlights the importance of data collection, cloud computing, real-time updates, predictive analysis, and proactive maintenance. These components differentiate DT from BIM by incorporating real-time data integration, simulation capabilities, and the ability to support proactive decision-making throughout the building’s lifecycle.

BIM and DT are related technologies, but they are not identical. BIM is a 3D digital model of a building that includes information about its design, construction, and operations. The evolution of DT from BIM can be traced to the increasing use of IoT, data analytics, and simulation tools in the AEC industry. With these technologies, BIM models have become more sophisticated, allowing for the creation of DT that can be updated in real time with data from sensors and other sources. It has enabled more effective decision-making, improved operational efficiency, and reduced costs in various industries.

4.3. Current Study to Compare Digital Twin with BIM

Over the past few years, the built environment disciplines, such as smart cities, building, construction, and mining, have placed considerable emphasis on the concepts of BIM and DT. While both concepts share similarities, they have distinct differences that set them apart. As stated by ThoughtWire [50], BIM emphasizes the system’s end-users more than DT does. The primary objective of BIM is to establish a digital replica of a building by establishing connections between virtual and physical data. BIM enables measuring and realizing changes in the current state of the physical building, but it is less advanced than the DT. On the other hand, DT is a newer concept and often needs clarification as more advanced applications of BIM.

The AEC industry has been discussing how to best advance the use of DT and BIM. Nevertheless, the differences and similarities between BIM and DT have yet to be agreed upon, as pointed out by Douglas et al. [35]. Both concepts have their strengths and limitations, and while BIM is designed primarily for the design and construction phases, DT is focused on the operational efficiency of assets [50]. One of the significant differences between BIM and DT is their ability to incorporate real time data from live sources. BIM models can simulate and predict future conditions, but their limited self-learning ability, autonomy, and external data processing have been criticized [50]. On the other hand, DT has the ability to assess present scenarios and execute foresight analyses while handling and supervising resources, thereby assisting in making decisions based on accurate data [35]. Sepasgozar [23] suggested that earlier digital modeling methods such as BIM have supplied digital information for construction, monitoring, or controlling physical objects. Still, the DT is expected to deliver beyond just a digital portrayal. It necessitates a two-way interaction between virtual and physical entities. DT models how people interact with built environments, and it includes real time data from sensors and other sources to reflect the current state of a building, infrastructure, or city. Boje et al. [7] mentioned that BIM is often treated as a sub-component of the DT, as it is the digital representation of the building, enriched by sensing capabilities, Big Data, and IoTs. Several important overlaps are identified from the conception of BIM during design, enrichment during construction, and completion towards becoming a valid DT [7]. The authors also proposed that it is essential to embrace a DT mindset for BIM to keep up with the latest integrated approaches on both micro and macro levels. The field of DT is much more advanced, incorporating physical and virtual elements interconnected by data.

Each technology has different characteristics that could influence the identification of advanced technology. By conducting a literature review of published studies and expanding upon the framework proposed by Khajavi et al. [21] and Feng et al. [30], this research suggested ten criteria regarding the comparative analysis, as shown in

Table 2. A detailed comparison of BIM and DT of building [21,30].

#	Items	BIM	Digital Twin in Building
1	Concept Origin	Dr. Charles Eastman (1970s)	NASA Apollo program (1960s) Dr. Michael Grieves (2000s)
2	Purposes	Used to enhance efficiency during design, construction, and throughout the building lifecycle	Used to enhance operational efficiency through predictive maintenance and monitoring assets
3	Application focus	Design visualization and consistency Class detection Time and cost estimation Lean construction Stakeholders’ interoperability	Predictive Maintenance What-if analysis Occupant satisfaction Resource consumption efficiency Closed-loop design
4	Features	Real time data flow is not necessarily required.	Real time data flow is not necessarily required
5	Level of Details	A detailed model of the building’s design and construction	Performance and optimization-focused real time building operation replica
6	Scalability	Depends on underlying technology and resources available for data processing and storage	More suitable for large-scale projects
7	Main Users	Complex and detailed, geared towards architects, engineers, contractors, and building professionals with high level of control and customization	Streamlined and intuitive, geared towards facility managers and operators with real time data and monitoring capabilities
8	Interoperability	3D model, Construction Operation Building COBie, IFC, CDE	3D Model, WSN, Data Analytics, Machine learning
9	Application interface	Autodek Revit, ArchiCAD, MicroStation, BIM Server, Grevit, Open Source	Autodesk Tandem, Predix, Dasher 360, Ecodomus, Siemens Digital Twin, Bentley iTwin
10	Building Life cycle stage	Design Construction Use (Maintenance) Demolition	Use (Operation)

Note: Our research has expanded the insights which were suggested by Khajavi et al. [21] and Feng et al. [30]. The additional data information is collected to identify these technologies based on the authors’ insights gained from reviewing the developers’ technical reports and related fields of literature. COBie: Information Exchange; IFC: Industry Foundation Class; CDE: Common Data Environment; WSN: Wireless sensor network.

. Selection criteria added a filter for study characteristics that helped determine whether they should be included, allowing researchers to analyze the data better. These criteria served as the attributes in the decision support framework, which thereafter will support stakeholders in making transparent decisions on identifying advanced technology in a construction project. A description of ten criteria can be added as follows:

• Concept Origin: technology’s origin is its history, goals, and principles. Understanding the concept helps researchers evaluate their strengths, weaknesses, and applications. The concept’s origin can also indicate which technological parts are more developed or need more research.
• Purpose: to define each technology’s scope and goals. This criterion helps determine their complementary roles and the best integration strategies to improve building design, construction, and operation.
• Application focus: It highlights each technology’s primary focus. It also shows each technology’s pros and cons to guide future improvements. It is crucial to choose the right technology for a project or application.
• Features: They are an essential aspect of the scientific comparison between BIM and DT, as they help understand each technology’s capabilities and limitations and their potential for integration and interoperability.
• Level of Details: We can assess the pros and cons of integrating these technologies into building projects.
• Scalability: allows for evaluating their ability to handle different types of projects and their potential limitations regarding resource requirements and integration with other technologies.
• Main Users: Identify each technology’s primary users and how it meets their needs. This information can help stakeholders choose technology based on project needs and team expertise.
• Interoperability: enables these technologies to be integrated with other systems and software, leading to greater efficiencies and improved outcomes in the building lifecycle management process.
• Application interface: evaluates the usability and effectiveness of the software for different users and applications.
• Building life cycle stage: compares BIM and DT in building construction, as it can help determine which technology is more suitable for a given project.

Our research has applied the proposed criteria, expanding upon the framework suggested by Khajavi et al. [21] and Feng et al. [30] to compare BIM and DT in the literature review. Table 2 clearly demonstrates the contrast between the utilization of BIM and DT modeling.

BIM and DT are two advanced technologies used in the building industry, with different purposes, application focus, features, main users, supporting technology, software, project lifecycle stage, and concept origin. Although there are some conceptual overlaps between BIM and DT, understanding how they relate is essential for developing DT within the built environment.

4.3.1. Concept Origin

BIM and DT concepts have distinct origins, with BIM originating in the 1970s through the work of Dr. Charles Eastman. In comparison, DT draws inspiration from the NASA Apollo program in the 1960s and further developments by Dr. Michael Grieves in the 2000s. Both concepts utilize digital technologies to enhance construction processes. However, DT goes beyond static modeling, introducing dynamic, real-time representations that enable performance monitoring, predictive analysis, and optimization throughout the building lifecycle.

4.3.2. Purposes

BIM is often considered the core technology for constructing a DT, but it needs to catch up to the concept’s continuous representation [5]. One of the significant differences between BIM and DT is their purpose. BIM focuses on improving efficiency during the design and construction stages [37], while DT’s main objective is to monitor physical assets and enhance their operational efficiency [39], enabling predictive maintenance [34]. The predictive simulation tools in BIM are designed for predictive use in design, while DT is used in operation and maintenance phases.

4.3.3. Application Focus

BIM is centered on enhancing the visualization of designs, ensuring uniformity, identifying different classes, promoting efficient construction [18], estimating costs and timelines [33], and promoting seamless collaboration [42] among stakeholders. BIM software includes Revit, MicroStation, ArchiCAD, Open Source, BIM Server, and Grevit. BIM includes design, construction, maintenance, and demolition throughout the project lifecycle stages. The concept of BIM originated in Charles Eastman’s work in the 1970s. On the other hand, through predictive maintenance and asset monitoring, DT can boost operational efficiency [39]. In DT, a physical object or system is represented virtually in a dynamic, digital form. It focuses on predictive maintenance, occupant satisfaction, resource consumption efficiency, what-if analysis, and closed-loop design [35]. DT software includes Autodesk Tandem, Predix, Dasher 360, and Ecodomus. DT is used mainly during the project lifecycle’s use stage. The concept of DT originated with NASA’s Apollo program.

4.3.4. Features

BIM and DT share some similarities but have distinct differences in their main features. BIM primarily aims to facilitate collaboration and create a digital model of a building or infrastructure project. Conversely, DT’s primary focus is to provide real time data from sensors embedded in a building or infrastructure project. Thus, BIM and DT can complement each other in the construction industry, enabling project stakeholders to create a digital representation of a building or infrastructure project, collaborate in real time [38], and monitor its performance over time [33]. However, a critical difference between BIM and DT is the need for real time data flow [18]. DT requires real time data flow to predict future outcomes and optimize performance [34], while BIM does not necessarily require it. As mentioned by Khajavi et al. [21], BIM is not designed to work with real time data, whereas DT heavily relies on it. BIM is a great tool for combining schedule and cost estimation information [37]. In contrast, sensor data collected in real time will be used in DT to better understand how occupants and their surroundings interact.

4.3.5. Level of Details (LoD)

This criterion is essential in comparing BIM and DT because it affects the extent and accuracy of the information that can be represented in the models. The LoD of BIM focuses on capturing the design and construction details [6], while the LoD of DT centers around real-time performance monitoring and optimization during the building’s operational phase [36]. While BIM is crucial for design coordination and information sharing, DT enables continuous monitoring, analysis, and optimization of the building’s performance based on real-time data feedback.

4.3.6. Scalability

BIM can be used for small- to medium-scale projects, whereas DT is more suitable for large-scale projects [35]. DT can handle a large amount of data and provide real time updates, making it easier to manage complex systems [33]. On the other hand, BIM may need to be able to handle the complexity of large projects due to limitations in its processing power and storage capacity. A study by Zhou et al. [20] compared the scalability of BIM and DT in construction projects. DT has more substantial scalability than BIM due to its capability to process massive amounts of information and deliver real time updates. Another study by Bolpagni et al. [40] highlighted the scalability of DT in the context of smart cities, where large quantities of data must be processed and analyzed in real time.

4.3.7. Main Users

BIM and DT have different primary users [37], with architects, engineers, contractors, and building professionals being the primary users of BIM, whereas architects, engineers, and facility managers are the primary users of DT. This difference can be attributed to the different purposes of the technologies, as BIM is primarily utilized in the initial stages of design and construction, whereas DT is commonly employed during the operational phase [36]. Additionally, BIM focuses on the physical and functional aspects of a building, while DT is centered on people and their interactions with the environment. As DT continues to evolve, it is expected to include entire organizations, with people, processes, and behaviors as essential data sources [50]. On the other hand, BIM is not designed to address operational questions related to optimizing operations [51].

4.3.8. Interoperability

BIM and DT require different supporting technologies and data exchange formats [18]. BIM depends on technologies such as 3D models, CDE, IFC, and COBie, while DT relies on technologies such as 3D models, WSNs, data analytics, and machine learning. Studies have compared the interoperability of BIM and DT and their ability to communicate and exchange data with other systems and applications. Boje et al. [7] found that BIM has higher interoperability with other systems and applications due to its open data exchange format, such as IFC. Still, DT can also achieve interoperability by Application Programming Interface (API) and data exchange standards such as Message Queuing Telemetry Transport (MQTT) and OPC Unified Architecture. Similarly, Bolpagni et al. [40] compared the interoperability of BIM and DT in building automation systems and found that both can achieve interoperability with open data exchange formats and protocols such as IFC and MQTT. Nonetheless, DT has an advantage over BIM in real-time data exchange [33] and integration with IoT devices [29].

4.3.9. Application Interface

The application interface of BIM and DT in the construction industry refers to the software platforms or tools commonly used to implement these technologies. BIM software platforms such as Autodesk Revit, ArchiCAD, and MicroStation provide comprehensive tools for creating and managing 3D models of buildings, including architectural, structural, and MEP elements, during the design and construction phases. DT application interfaces, including Autodesk Tandem, Predix, Dasher 360, Ecodomus, Siemens Digital Twin, and Bentley iTwin, are specialized for operating digital replicas of assets during the operational phase, using real-time data for optimization and maintenance.

4.3.10. Characteristics

According to Shahzad et al. [25], there were some conceptual overlaps between BIM and DT. To ensure DT’s future progress within the built environment, it is crucial to have a comprehensive grasp of how these elements are interconnected. Douglas et al. [34] recognized three commonly found interpretations in the literature: DT is viewed as a progression and improvement of BIM; BIM and DT are seen as distinctly different concepts because of several notable variations; and BIM and DT are characterized as two interrelated ideas.

Table 3. Compare the characteristics of BIM and DT [25].

#	Items	BIM	Digital Twin	Sources
1	3D model visualization	Yes	Yes	[1,30]
2	Reliance on CDE	Yes	No	[7,18]
3	Reliance on IFC	Yes	No	[2,40]
4	Reliance on WSN	No	Yes	[11,40]
5	Reliance on Data Analytics	No	Yes	[29,42]
6	Reliance on Machine Learning	No	Yes	[5,11]
7	APIs Interoperability	Yes	Yes	[34,41]
8	COBie Interoperability	Yes	Yes	[7,34]
9	Data standardization	Yes	Yes	[25,40]
10	Data exchangeability (two-way communication)	No	Yes	[25]
11	Scheduling	Yes	Yes	[7,36]
12	Architects, Engineers, and Contractors interface	Yes	No	[5]
13	Facility Manager/Operator interface	No	Yes	[37,40]
14	Focus on Collaboration	Yes	Yes	[1,27]
15	Focus on Real-time data	No	Yes	[11,18]
16	Focus on Design and Construction	Yes	No	[18,40]
17	Focus on Building Operations	No	Yes	[11,24]
18	Focus on Physical & Functional Aspects of Building	Yes	No	[12,21]
19	Inclusion of People, Processes, and Behaviors	No	Yes	[18,22]
20	Time management	Yes	Yes	[11,25]
21	Budget management	Yes	Yes	[25,27]
22	Project simulation analysis	Yes	Yes	[25]
23	Simulation analysis in context	No	Yes	[25]
24	Live monitoring of assets	No	Yes	[25,40]
25	Live and instant updates on equipment status	No	Yes	[25]
26	Instant response to equipment failures	No	Yes	[25]
27	Insights to increase building use and performance	No	Yes	[40]
28	Overall project time and cost reduction	Yes	Yes	[11,41]
29	Easy application on existing buildings	No	Yes	[25]
30	Better value for employers	Yes	Yes	[36,40]
31	Improved building sustainability	Yes	Yes	[11,36]
32	Dynamic construction risk management improved	No	Yes	[11,12]
33	Enhance site logistics	No	Yes	[7,12]
34	Use of machine learning and automated processes	No	Yes	[11,40]
35	Use of self-learning algorithms	No	Yes	[25,35]

Note: Our research has expanded the insights which suggested by Shahzad et al. [21] and Feng et al. [30]. The data are collected to identify these technologies based on the authors’ insights gained from reviewing the developers’ technical reports and related fields of literature. CDE: Common Data Environment; IFC: Industry Foundation Class; WSN: Wireless Sensor Networks; ODE: Ordinary Differential Equations; APIs: Application Programming Interfaces; COBie: Construction Operations Building Information Exchange.

compares the characteristics of BIM and DT in building construction. BIM and DT enable 3D model visualization, achieve interoperability with open data exchange formats, APIs, and data exchange standards, and focus on collaboration and project management aspects such as scheduling, budget management, and project simulation analysis. However, there are notable differences between the two technologies, such as the reliance on wireless sensor networks, data analytics, and machine learning, which are more prevalent in DT. At the same time, the user interface of BIM is geared toward architects, engineers, and contractors, and DT is geared toward facility managers and operators. Other differences include the focus of BIM on design and construction phases, physical and functional aspects of buildings, and the inclusion of people, processes, and behaviors. In contrast, DT’s primary focus is creating efficient building operations and utilizing real time data. It provides live monitoring of assets, quick updates on equipment status, and immediate response to equipment failures. Additionally, it offers valuable insights to enhance building utilization and performance while reducing project time and cost over the project life cycle. Ultimately, its services promote improved building sustainability. In addition, DT uses machine learning and self-learning algorithms. Apparently, BIM and DT have their strengths and limitations, and they can complement each other to provide a comprehensive solution for building construction projects. Still, studying the literature has shown that there are challenges to integrating them, such as the lack of standardization and the need for more research in this area.

4.4. Advancement of BIM to Improve Digital Twin in Building Construction

BIM has advanced in recent years to support the creation and improvement of DT. Some of the critical advancements include the following:

• Increased interoperability: BIM technology has become more interoperable, allowing seamless data exchange between platforms and systems [7]. It makes creating and updating DT easier with real time data from sensors and other sources.
• Improved data accuracy: BIM technology can offer precise and comprehensive insights into a building’s blueprint, building process, and maintenance, all of which can contribute to developing a more precise DT [12].
• Increased collaboration: BIM enables collaboration among architects, engineers, and construction professionals, leading to better decision-making and improved overall outcomes [25]. When this collaboration is applied to creating a DT, it can result in a more comprehensive and effective virtual representation of the building.
• Better visualization: BIM technology has advanced to include more realistic and interactive visualizations [40], making it easier to understand and analyze the building’s performance through the DT [11].
• More advanced simulation: BIM has also advanced to include more advanced simulation capabilities, allowing for the simulation of complex systems and analyzing building performance in real time [40].

Using evolving BIM methodology to achieve BIM is a unique and essential feature presented by DT, as they comply with the AEC industry. BIM systems rely on creating a complete parametric model that is centralized and unique to the projected building or infrastructure [26]. This model consists of all the necessary elements required for construction, and each element is defined by specific parameters such as materials, geometry, and constructive systems. With BIM systems, elements are projected and included in the model, estimating and sizing all design parameters rather than representing them in simple drawings. It allows for a digital construction of each element and its relationship with the environment. Additionally, the model is prepared for specialists and contains all the necessary information for constructing infrastructures or buildings, including materials, estimations, constructive systems, and measurements [26].

5. Result and Discussion

5.1. Result and Discussion

The comparative analysis of DT and BIM in building construction has been extensively studied in recent years, with numerous studies examining their characteristics, supporting technologies, interoperability, and scalability. The results of these studies have shown that both DT and BIM have unique strengths and weaknesses that make them suitable for specific use cases and project phases. One of the main differences between DT and BIM is their focus, with DT primarily used for building operation and maintenance, while BIM is used for the design and construction phases. This difference is reflected in their supporting technologies, with DT relying on wireless sensor networks, data analytics, and machine learning, whereas BIM relies on 3D models, common data environments, and industry foundation classes. Another critical factor to consider when choosing between DT and BIM is their interoperability and scalability. While both can achieve interoperability through open data exchange formats and APIs, DT has an advantage in real time data exchange and integration with IoT devices. Even so, the scalability of DT depends on the underlying technology used and the resources available for data processing and storage.

Based on the findings of the comparative analysis, it is recommended that building professionals carefully consider the specific needs of their project when choosing between the two. BIM is the preferred technology for projects that focus on the design and construction phases, given its ability to provide high levels of control and customization in modeling workflows. However, DT is the better choice for projects that focus on building operation and maintenance, given its ability to provide real-time data and monitoring capabilities. Furthermore, it is recommended that building professionals explore the potential of combining both DT and BIM technologies to achieve greater project efficiency and effectiveness. For example, BIM models can create DT that provides real time data for building operations and maintenance. Additionally, the interoperability of both technologies can be improved by using open data exchange formats and APIs.

The study presents 30 relevant papers on BIM and DT in the construction industry. These 30 studies utilize various research methodologies such as literature reviews, case studies, interviews, questionnaires, conceptual analysis, and experimentation. Key findings highlight the potential benefits and challenges of DT implementation, the relationship between BIM and DT, and the applications of DT in construction. Common themes include the need for data integration, information standardization, and advanced technologies to support DT implementation. DT offers real-time decision-making, self-operation, remote supervision, and improved efficiency in various construction lifecycle phases. Challenges associated with DT implementation include data interoperability, security, funding, skilled professionals, and information standardization.

DT extends beyond the capabilities of BIM by incorporating real-time data from sensors and IoT devices. The main research objective of this study was to conduct a comparative analysis between DT and BIM in building construction. We examined their similarities and differences through a comprehensive literature review, exploring their unique features and contributions. The applications of DT and BIM in building construction are diverse and mutually beneficial, with BIM providing efficient project management and collaboration. At the same time, DT enhances decision-making and performance optimization through real-time data integration. The integration of these technologies holds immense potential for transforming the construction industry, enabling stakeholders to achieve better project outcomes, improved sustainability, and enhanced building performance. In conclusion, by elaborating on the present applications of DT and BIM, the research aims to emphasize their significance in the context of this research.

5.2. Limitation

Several available technologies support the utilization of DT in the construction industry, including BIM, wireless sensor networks, data analytics, and machine learning. BIM is progressing rapidly with the help of technological advancements, and it is now comparable to DT preparation. Moreover, it is essential to note that BIM only provides a static model of the structure or building. To fully utilize the benefits of DT, the model must be self-reliant, self-updatable, and self-learning. According to El Jazzar et al. [24], although the term “Digital twin” was not explicitly mentioned in the reviewed literature, the content aligned with the concept of DT. As a result, the framework proposed by the researchers aims to assist the construction industry in comprehending the degree of digital transformation maturity in construction by classifying the present literature based on the classification of DT implementation in manufacturing by Kritzinger et al. [52]. As noted by El Jazzar et al. [24], most of the reviewed publications were categorized under the Digital Shadow subcategory, indicating that BIM methods are expanding beyond design and construction with digital models. However, there is a need to shift towards a fully integrated DT that monitors and collects data, takes corrective measures, and predicts potential emergencies. El Jazzar et al. [24] recommend that the construction industry recognize the potential benefits of a fully integrated DT and work toward its implementation. As Seaton et al. [18] note, BIM has become a part of almost every aspect of the construction process. Therefore, for DT to be accepted, they must provide value and benefits beyond what is currently possible with BIM and other model-based and data-driven work practices.

The use of DT in the AEC industry has the potential to transform construction site management. DT can automate resource allocation and waste management and simulate site, material, machinery, and working conditions in a virtual environment [53]. It is made possible by integrating live data sources, a feature that BIM processes and technologies lack [50]. Nevertheless, the successful execution of DT encounters various obstacles, such as the lack of accessible technology, inconsistencies in data standards, concerns surrounding data protection and ownership, the need for employees to learn new skills, and the vital requirement for a shift in the cultural mindset. BIM and DT have similar development and adoption journeys, and the challenges faced in the development of BIM can provide insights into the development of DT. In particular, the lack of common data standards and tools has challenged both concepts [35].

5.3. Future Study

The authors suggested that in the coming years, the sector and the profession will see the technologies that underpin DT continue to mature [18]. For instance, sensors, machine vision, data governance, modeling, and visualization technologies promise to make DT more powerful, useful, and easier to create and maintain. New additions to the scene, such as augmented reality and virtual reality-enabled “metaverse”, are expected to be part of these developments. DT is a promising concept that can potentially revolutionize the construction industry. The current trend in the industry is towards utilizing Digital Models in design and construction, but there is a need to move to a fully integrated DT that not only collects data but also takes corrective measures and predicts potential emergencies. Future technological developments, such as sensors, machine vision, data governance, and modeling, promise to make DT more powerful, useful, and easier to create and maintain. The construction industry must recognize the potential benefits of a fully integrated DT and work toward its implementation.

BIM is essential for building construction, providing data integration capabilities and foundation for DT. Future research should focus on enhanced integration, advanced data analytics [29], lifecycle management, interoperability [34], sustainability, energy efficiency [21], user experience, and integration with smart cities [40]. By integrating BIM with real-time sensor data, IoT devices, and monitoring systems, researchers can improve decision-making and DT functionality. Additionally, research should explore human-centered design principles, user experience, and integration with smart cities to enhance collaboration, communication, and project success.

Another topic should focus on resilient Digital Twins, which integrate resilience principles and practices into the DT framework. A resilient DT can contribute to a low-carbon, climate-resilient future [26] by implementing sustainable design, energy management, climate adaptation, and resilience control [23]. By utilizing machine learning and AI, the twin can monitor and control building systems, optimize energy efficiency, and support decision making. By addressing these areas, researchers can unleash the full potential of DT to create more sustainable built environments.

6. Conclusions

This research contributes to the body of knowledge by clarifying and differentiating the DT concept from BIM through a literature review based on proposed research questions. The research has achieved three main objectives: (1) examining the present applications of DT and BIM in the construction industry; (2) emphasizing the similarities and differences between DT and BIM; and (3) developing solutions and design methods for the integration of BIM and DT in building construction. In addition, the study develops ten criteria for the comparative analysis between DT and BIM, including the concept origin, purpose, application focus, features, level of details, scalability, main users, interoperability, application interface, and building life cycle stage. The study adopted and built upon the framework developed by Khajavi et al. [20] and Feng et al. [29]. Most significantly, the framework proposed in our research advanced the prior works by adding four criteria—purpose, features, level of detail, and scalability—which helped establish a clear and objective framework for evaluating their similarities and differences. By using the framework, this research helps practitioners and researchers assess the strengths and weaknesses of each technology and make informed decisions on which one to use in each context. Further, this research concluded that by applying an integrated DT and BIM platform, the AEC sectors could better assess and develop the design, construction, and performance, optimizing energy design, reducing costs, and reducing environmental impact in building construction. The focus of the research has shifted toward DT, and necessary data collection and connection to BIM, including sensing data, is necessary to achieve this change. DT can reduce energy demand during construction and operational phases, decrease rework and approval cycles, and increase transparency and collaboration. DT applications can help address issues in the construction industry. Facilities managers can access digital models of facilities operating in real time, improving decision-making for optimum performance. BIM is best suited for construction and design, while DT is best suited for building maintenance and operations. As the industry continues to evolve, there will be an increasing need to leverage these technologies to stay competitive and meet modern construction demands. Future research is needed to expand and enhance the integration of DT and BIM throughout all building life cycles.