COMMENT A digital twin is a unified data model representing the dynamic state of a building, integrating as-built information with data from multiple smart building systems. This unprecedented interoperability enables data-driven workflows to optimise asset performance, occupant experience and carbon. Or put simply, it is an accurate, dynamic digital replica of the physical asset.
The reason digital twins are important for real estate and the industry is getting excited about them lies in reducing risk, decreasing Opex and increasing yield.
Imagine if you could automate your business processes using standardised information that you, your employees, and supply chain can trust. Imagine having data to alert you that a tenant is going to vacate your premises before they know it. Imagine a reduced-risk business that is delivering on yield, satisfaction and ESG. Pipedreams? Maybe not.
Why this is no pipedream
For years, manufacturers like Tesla and Boeing have used digital twins to create digital replicas of cars and aircraft. They do this to understand the performance of their products in the field. Digital twins give them access to all the metadata and dynamic data (via sensors) of their products and how users interact with them. The value is they have, at their fingertips, the information to quickly understand what is working, what is not working and quickly course correct where necessary.
However, a manufacturing process is repeatable and its supply chain is much more synergistic than real estate. In the built environment, one size does not fit all. Buildings are designed to meet specific objectives, project teams assemble, and the asset is built. After handover, the teams move on to their next job. Each company has its own tools and processes and, of course, there is no willingness to invest in technologies to benefit others in the supply chain.
There is no silver bullet, but a programmable digital twin platform can integrate all those different tools, to ensure that information can flow freely from one source to another, throughout the project lifecycle.
A digital twin is not static but evolves progressively with the lifecycle of the building. For example, in a new development, the digital twin journey ideally starts with defining the use cases before design starts, which, in turn, helps identify data required throughout the project.
In design, data can be used for simulations, material sustainability assessments, and analysis for design optimisation, to name just a few examples. As the project matures, construction information, mechanical, electrical and plumbing system and equipment data help owners plan for maintenance and operations.
Ultimately, this information results in an “asset twin”, which delivers a complete, detailed online manual of the facility at handover. When you add dynamic, operational data (from a BMS, IoT systems, fire detection systems, maintenance systems, etc), the digital twin is born. In this example, with a new facility, you can take a sequential approach starting with the use case definition and information requirements, maturing through the process, ending with a new facility plus its digital twin replica.
What about existing buildings?
Obviously the same approach cannot be taken with existing buildings. Here, you have to look across multiple, fragmented sources for the building information. More often than not, this information can be fraught with problems. However, you can still achieve a trustworthy and effective digital twin with proper planning.
Like new developments, the starting point of an existing building’s digital twin must be use case-driven, along with a keen focus on ROI. This will help you to create a data model for your building to address the problems you want to solve. Often, owners look to extend equipment lifespan, reduce energy use, or improve occupier productivity and wellness.
Data modelling is key
Whether it’s a new or existing building, data modelling is crucial to the success of the digital twin. Key “building blocks” in an effective data model include the spaces in the building, the systems that serve those spaces, the critical assets in those systems, the sensors that capture the performance of those assets, and the meters that measure energy use, for example. With this data, you can start to understand how, where, and why energy is being used.
Digital twinning will essentially enable real estate owners to create an automated, dynamic and standardised system for all aspects of running their portfolio. Just as digital twins were game changing in the manufacture of cars and aircraft, so they will be game changing in the real estate industry. They will allow owners to understand the performance of their buildings, remotely and in near real-time. The ability to automate reporting, improve environmental and sustainability performance, refine design requirements, satisfy tenants, produce standardised and trustworthy data – the list goes on – will result in lower Opex, increased yield and a reduction in risk.
Claire Penny is global digital evangelist at Invicara
