Harnessing digital twins to transform the connected built environment

BIM is as an essential foundation for digital twins. The detailed 3D models and data generated through BIM processes form the basis for the virtual representation of the asset in a digital twin. However, simply having a BIM model does not equate to having a digital twin.

A digital twin is a digital representation of a physical asset, process, or system, enriched with continuous data. Unlike static BIM models, digital twins are dynamic and interactive, allowing users to visualise, monitor, and optimise assets in real-time. They are connected to the physical asset through sensors, Internet of Things (IoT) devices and other data sources, enabling continuous data flow and analysis.

The transition from BIM to digital twins involves enriching these models with real-time data from various sources. This data integration requires:

• Developing an information management framework that outlines data requirements and standards for digital twin creation.
• Implementing a common data environment (CDE) to manage and share data across all stakeholders.
• Integrating BIM data with real-time data sources using APIs and other relevant technologies.
• Adopting open data standards, such as industry foundation classes (IFC), to ensure interoperability between different systems and platforms.

The sophistication and capabilities of digital twins can vary greatly. There are different levels of digital twin maturity:

• Pre-digital twin: Created during the upfront engineering, it is a virtual prototype of the envisioned physical asset. The elements, their respective relationships, and actual data are created as early as the planning and design stage, then carried over through to the end of the construction phase. This helps designers and engineers to plan and mitigate risks in the design and construction stage. Currently, the industry refers to these models as BIM or digital models.
• Informative digital twin: A virtual replica of the completed physical asset that captures similar characteristics of the Pre-Digital Twin and incorporates maintenance, asset condition, finance, resources, and performance data of the physical asset.
• Performance digital twin: Connects digital and physical versions of the asset using sensors or IoT devices. This allows for real-time data of the physical assets to be reflected in the digital model. This allows information like status data, performance, and operational health from the physical asset to be constantly monitored.
• Autonomous digital twin: Automates discovery of new knowledge and insights through data mining and machine learning, which enables it to continuously learn and improve over time. This generates predictive insights from the asset which lead to reduced downtime, optimised energy consumption, and the development of new business models that foster continuous optimisation processes and deliver true value.

Digital twins offer a wide range of benefits across the asset lifecycle:

• Improved design and construction: Digital twins can be used to simulate and analyse different design options, identify potential risks and clashes, and optimise construction sequencing, leading to reduced costs and improved project outcomes.
• Enhanced infrastructure resilience: By providing real-time insights into asset performance, digital twins enable proactive maintenance, optimise energy consumption, and extend asset lifespans.
• Data-driven decision making: Digital twins provide a single source of truth for asset information, facilitating informed decision-making for operations, maintenance, and future investments.
• Increased collaboration and communication: Digital twins provide a shared platform for stakeholders to access, visualise, and analyse asset information, fostering collaboration and improving communication across teams.

Outside of some specific industries which have experienced digital maturity for some time, digital twin is in its infancy more broadly. Some projects have used various capabilities that digital twin systems provide to enhance the way they design and deliver projects, prepare for handover to operations, or coordinate daily operations and asset management.  
 
GHD has been actively involved with several clients in their journey to transform their business and manage data better, along their digital twin journeys. For example, we are working with several municipal water agencies to digitalise their sites. They are doing this to improve their understanding of the condition of their current assets, improve assessment of how their assets are functioning and help them prepare for future demands – both in preparation for water security and increased demands, along with legislative changes, such as PFAS requirements.
 
Many agencies are undergoing digital transformations, driven by evolving industry standards like ISO 19650, and leveraging the power of AI to improve project delivery, asset management and operational efficiency. In the rail industry, transit agencies are exploring how digital twins can help optimise asset management, reduce costs and mitigate risks associated with aging infrastructure. For example, in the UK, we are supporting Network Rail in the shift to a digital railway. The initial work is targeting improved collection, integration and use of data to support earthwork inspections and minimise risks of slope failures. This solution is enhancing inspection activities by streamlining and automating processes along with providing greater coverage of site studies. The team has developed a spatial online visualisation tool that allows remote full-site inspection and instantaneous comparison of the changing conditions along the track, ensuring effective mitigation measures to be implemented quickly.

We also worked with Wellington City Council (WCC), a pioneer in smart cities and digital twins, to help gain deeper insight into how digital twin capabilities could be leveraged for insights into housing development planning, yields and feasibility. We helped WCC realise the different density scenarios and their impact and explore questions like how expansion plans might impact water requirements, energy use, CO2 emissions and the impact of density on the broader area, such as transport and green space through the implementation of a GIS and data driven digital twin solution.

While digital twins hold immense potential, their implementation comes with challenges:

• Data management: Managing vast volumes of data from diverse sources raises concerns about data quality, security and interoperability.
• Cost and complexity: Developing and maintaining digital twins demands investment in technology, expertise and resources.
• Lack of standards: The absence of widely adopted standards for digital twin creation and data exchange can hinder interoperability and limit their value.
• Cybersecurity risks: Digital twins, being complex systems with numerous interconnected components, can be attractive targets for cyberattacks, potentially leading to data breaches, system disruptions and financial losses.

However, these challenges present opportunities for growth and innovation:

• Advancements in technology: AI, machine learning and cloud computing are making digital twins more accessible and manageable.
• Industry collaboration: Organisations are working together to establish open standards and best practices for digital twin implementation, promoting a more connected and interoperable built environment.
• Focus on systems thinking: Digital twins encourage a holistic approach to asset management and decision-making, leading to better outcomes across systems.

The journey from BIM to digital twins represents a significant leap forward for the built environment. By harnessing real-time data, interconnected models and AI, organisations can achieve new levels of efficiency, resilience and sustainability. To fully realise the benefits of digital twins, the industry must prioritise information management, collaboration and the adoption of open standards. These efforts will lay the groundwork for a more connected, intelligent and responsive built environment that serves all stakeholders.

This is a pivotal moment for the industry to wholeheartedly embrace the digital transformation and shape the future of the built environment. By working together, we can create a more sustainable, resilient, and prosperous world for generations to come.