The fast deployment of digital twins within the built environment shows how technologies could contribute to the optimisation of the construction project life cycle. Against the backdrop, Dr Georgios Kapogiannis, Head of Thought Leadership in Glodon, gave an in-depth online lecture about digital twins under the invitation of Dr Konstandinos Papadikis and Dr Cheng Zhang of the Xi'an Jiaotong-Liverpool University (XJTLU).

In addition, he presented the results of the joint research report conducted in partnership with RICS in the United Kingdom.

A virtual journey to Xi'an and Glodon's R&D Building also took place, where Dr Kapogiannis provided the audience with a demonstration showing holistically how the digital twins are taking shape and how they can really drive the management of the project life cycle.

Defining the digital twins

According to the report, commonly used terms that emerge from these definitions of a digital twin are: virtual or digital representation; real-world entities, processes or physical assets, or elements; realistic representation; synchronisation, including synchronisation frequency and fidelity; monitoring performance; insights and intervention. While the mirrored world may still be a distant dream, digital twins can be applied with an increasing level of sophistication or maturity. Some experts see this at five levels of complexity or sophistication of digital twins starting from:

?descriptive digital twins (for collecting and visualising data)

?informative digital twins (converting data into information for generating insights)

?predictive digital twins (using real-time data to predict future state)

?comprehensive digital twins (combining levels 1, 2, and 3 to propose interventions for avoiding problems and achieving better outcomes)

?autonomous and connected digital twins (using artificial intelligence (AI) and machine learning (ML) to reduce dependence on human intervention)

Added value of digital twins in design, construction and handover

In addition, Dr Kapogiannis highlighted how digital twins can help the design, construction, and handover process based on the responses from the survey and the interview.

In particular, he mentioned digital twins can improve the design, construction, and delivery of new assets and integrates existing assets and conditions in the design and construction process, while also enhancing the handover process by verifying as-built conditions with as-built data and information.

According to him, digital twins also streamline the materials supply management and integrate the life cycle steps and the input of project team members. It makes use of historical data and information from downstream processes in design and construction.

Another advantage of the digital twins is improving investment and financing decisions by simulating economic considerations in conjunction with environmental, social, and governance criteria. And it also helps reduce errors, rework, and fragmentation in work practices by providing access to real-time work performance data from the construction site.

By facilitating the timely intervention of emerging risks, digital twins enable increasingly predictable cost and schedule outcomes during project execution. And reducing life cycle costs by enhancing time and cost certainty of the delivery process.

Other added value of digital twins can be increasing productivity and operational efficiency and enhancing collaboration across the project team during the design, construction and handover processes; improving worker safety, health and wellbeing by providing actionable insights.

What's more, digital twins can help reduce environmental impacts, primarily by reducing upfront embodied carbon emissions by comparing options. And they also reduce overall life cycle costs and carbon emissions through timely and tested interventions and improved asset performance through efficient design, construction, and handover processes.

Emerging technologies influence the future of digital twins

In addition to the above, Dr Kapogiannis mentioned how emerging technologies influence the future of digital twins through:

Computer Vision: including presence or absence of materials, products, equipment, etc.; extraction of quantities of materials and sub-assemblies; movement of workers, plant, equipment and products; presence or absence of safety equipment, especially personal protective equipment (PPE) and progress or completion of work put in place, including quality assurance and control.

Data fusion: Digital twins require multiple data sources to extract timely and actionable insights. Data fusion removes the burden of processing the raw data from various sources so the end-user can focus on the insights.

Artificial intelligence and machine learning: The amount of data and information available within a digital twin system is not manageable by humans without the aid of computer tools to assist in data processing, analysis, and sense-making. AI and ML synthesise the data within a digital twin system and converts it into a human consumable format.

Digital platforms: No single out-of-the-box solution can be used to create digital twins. While a platform approach is preferable, and several are being developed (for example, see below figure), it is realistic to expect that full-cycle digital twins will include products and data connections to multiple products and phase-specific platforms. A digital platform (or ecosystem) combines products, software, concepts, ideas, or thinking that is open to end-users and other firms (complementors) to extend and create value-adding solutions. In the case of digital twins, a BIM-based platform (e.g. the openBIM initiative started by buildingSMART) may become the core product with boundary objects or modules (e.g. application programming interface, software development toolkit, etc.) available to develop complementary products and apps.

Source:? Glodon Digital Building Platform White Paper Compact Edition

Internet of Things: IoT and sensors can play an important role in a digital twin. But currently, IoT sensors are complex for field teams to specify, install and maintain throughout an ever-evolving construction site and asset in use. As the value of the data and analysis that these sensors can support becomes more commonly understood, some of the resistance to installing and maintaining a network of sensors may subside, and direct and indirect costs will reduce.

Simulation: With an abundance of data available from a digital twin, the ability to conduct what-if analysis increases. For example, AI-driven what-if simulations of a construction project schedule based on historical project data can provide insights into any likely delays and related cost overruns that the project may encounter based on current performance.

Collaborative work practices: Digital twins both promote collaboration and require collaboration. Previous studies have shown the importance of developing a collaborative culture in construction enterprises using integrated collaborative technologies. Considering digital twins are an integrated collaborative environment that use state of the art digital technologies, they can support superior decision making and better project, asset and business operations. Identifying, developing, and managing collaborative business relationships within or between organisations is crucial for digital twins' progress in the built environment sector to support information-based decisions and collaborative behaviour.

Supply chain management: Modern construction sites are seeing a wave of innovation and interest in how products, materials, components, etc., are supplied to the job site. Visibility of prefabricated components produced on-site, near-site, or offsite is helping enhance worker safety, productivity, and predictability. RFID, machine vision, and other label-based means of this real-time data when integrated into a digital twin system means project teams can use automated progress monitoring to manage risk and forecast performance.

Skills and competencies: People will play a central role in the progress of digital twins. They will benefit from the development of digital twins, especially an ecosystem of connected digital twins for the built environment. People will also play a central role in creating, deploying, using and updating digital twins. This will require new skills, competencies and pathways to enter the profession. Without investing in people, the industry cannot fully realise the benefits of digital twins.

Expecting the future

As a final note, Dr Kapogiannis mentioned that over 60% of the chartered construction and QS and project management professionals who responded to the survey do not currently use digital twins. However, digital twins are expected to continually develop as a critical tool in all phases and the overall asset life cycle, especially considering continued environmental, social and governance (ESG) requirements.

So, in the coming years, the sector will see the technologies that underpin digital twins continue to mature. Sensors, machine vision, data governance, modelling and visualisation technologies promise to make digital twins more powerful, useful, and easier to create and maintain. Entirely new additions to the scene, such as AR- and VR-enabled' metaverse', are expected to be part of these developments, but so would ubiquitous laser scanning, AI-powered voice data collection, and other developments perched on the horizon.