Digital Twins: from space to the home

Introduction

The idea of a digital twin may stem from the explosion of an oxygen tank in the Apollo 13 space mission of 1970. “NASA employed multiple simulators to evaluate the failure and extended a physical model of the vehicle to include digital components. This “digital twin” was the first of its kind, allowing for a continuous ingestion of data to model the events leading to up to the accident for forensic analysis and exploration of next steps” (NASA, 2021). The importance of accurate digital models is clear in programs such as Artemis, which is intended to facilitate missions to Mars, when the constant communication needed to allow human intervention in case of problems will not be available.

Digital twins also have many earth-bound applications such as product research and design, replacing costly prototypes; supply chain operations, giving manufacturers a comprehensive view of logistics, operations and potential bottlenecks; collecting data about products and their use, allowing manufacturers to make continuous improvements; and in providing safe staff training.

An article in Manufacturing Digital outlines the complexity of digital twins, which can include 3-dimensional computer-aided design files, sensors connected to the Internet of Things (IoT), and augmented reality visualisation. “They are in essence an ecosystem of data communication” helping manufacturers to analyse their present and past and to predict the future. Digital twins can also monitor and analyse the carbon footprint of operations, helping manufacturers to meet environmental standards (MD, 2024).

The following paragraphs will emphasize the application of digital twins to the built environment.

Defining a digital twin

An article from the CTO Academy describes a digital twin as “a virtual representation of a physical asset, system or process that uses real-time data, simulation and analytics to mirror its real-world counterpart” (CTO, 2025). Creation of the digital twin involves “integrating multiple data sources, including sensors, IoT devices and historical records, to generate a detailed model of the physical asset.” Four stages of operation are described: appropriate data is collected from sensors in real time; computational models simulate the behaviour of the system; analytic tools and machine learning process data “providing insights into performance and potential issues”; and the digital twin is continuously updated to maintain the accuracy of its representation of the physical system.

Depending on the application, a digital twin may assist predictive maintenance, remote troubleshooting and diagnostics, simulate behaviour under extreme conditions, and help to optimize processes. The general challenges faced by digital twins include data integration, data security and high implementation costs. CTO cited Singapore’s 2014 digital twin project as an application to “urban planning, integrating traffic data, infrastructure models and environmental analytics”. Security risks were addressed through cybersecurity measures and data privacy regulations, and the city “successfully optimised traffic flow, reduced emissions, improved public services and even facilitated disaster management.”

Digital twins and buildings

“From planning to construction and eventually the operation of a building, huge amounts of data are created by multiple stakeholders. However, this valuable information resides mostly in silos and thus becomes inaccessible throughout a building’s lifecycle … outdated and incomplete information leads to poor and error prone decisions which negatively affect buildings’ performance and increase operational costs” (Nemetschek, 2024).

Under the heading of Sustainable Buildings, the company claims that “40% of CO2 emissions are caused by buildings and structures” and estimates that “30% of all construction work is spent fixing planning errors.” It sees its digital twin platform as a way of bringing together information from Computer Aided Design and Building Information Modelling software, Integrated Workplace Management Systems, and real-time data to enable “true Building Lifecycle Intelligence”.

The projects shown on the company’s website are mainly large scale: airports, railways and ports; large commercial, residential and educational buildings; healthcare and sports facilities. Smaller projects are discussed below.

Micro and macro digital twins

“In the context of the United Kingdom’s housing sector, Digital Twins are making significant waves, bringing transformative changes to the way we design, construct, and manage homes and their underlying infrastructure” (HUBBPRO, 2025). In this article, two distinct categories of digital twin are distinguished: micro and macro. “Micro Digital Twins focus on individual houses or residential units” whereas Macro Digital Twins can “encompass entire housing developments”. The digital twin of an individual house is a detailed and accurate digital replica, useful in design, construction, maintenance and smart home integration; for a housing development, the digital twin provides a “holistic view of housing ecosystems, including the interplay of energy, utilities, and infrastructure at … community level.”

The micro digital twin of an individual house can be used to “optimise layouts, energy efficiency, and aesthetics” at the design stage. It can help to ensure “precise construction by providing builders with accurate 3D models that guide the construction process.” By providing a “digital record of the building’s components” it makes it easier to “identify maintenance needs, plan repairs, and track the performance of systems like HVAC and electrical.” It also helps to optimise energy usage, by “monitoring the real-time performance of heating, cooling, and lighting systems” giving a basis for informed decisions on reducing energy consumption and utility costs. Digital twins also “enable seamless integration of IoT devices, making it possible to control lighting, security, and climate systems remotely” and to simulate changes in the house to “assess the impact on energy consumption and comfort.”

The cost of a digital twin

Some idea of costs for digital twin projects in buildings, together with estimated payback times, is given in a report from the Consulting Engineer Survivor, which estimates the cost of a digital twin project for a school of around 300,000 ft² at between $290k and $410k with a payback period of 5 years (CES, 2025).

The National Institute of Standards and Technology suggests that a digital twin for a high-tech factory or laboratory building would “cost between $510 000 and $720 000 and has a 9-year payback period”, and the corresponding cost for a general hospital would be “between $2.9 million and $4.2 million with a 4 year payback period”. The payback benefits are primarily in operations and maintenance. For small projects, the cost could be between $20k and £45k for the software application, plus the cost of sensors, data standardisation and implementation. (NIST, 2024).

Digital twins and retrofit

Built Environment – Smarter Transformation, or BE-ST, is an innovation centre in Scotland which promotes the built environment’s transition to zero carbon emissions. It aims to revolutionise the approach to retrofit & building upgrades, stating that retrofitting existing buildings “is a complex challenge. Every building is unique, and each retrofit must respond to its specific materials, systems, and patterns of use.” The process too often relies on assumptions, and to avoid mistakes “we need to understand how the building truly performs today, not just its fabric and services, but also how size, orientation, and usage affect energy demand” (BE-ST, 2025).

Retrofit approaches at 14 sites in the UK were part of the Alchemai project, which addressed at scale “the barriers which exist for non-domestic estate owners to decarbonise their buildings.” Digital Twin technology, building performance expertise, and immersive visual tools were combined to help building owners optimise their retrofit decisions “reducing risk, avoiding costly mistakes, and ensuring the right upgrades are delivered at the right time.” The final report on the Alchemai project is available via the BE-ST website, cited above.  

Virtual sensors

The term virtual sensor is often used in connection with Digital Twins. Information provided to the software by physical sensors can be used to estimate the value of parameters which are not directly measured; the combination of physical sensors and software acts as a “virtual sensor”. An example is the use of physical sensors reading temperature and relative humidity. The software can use their input to calculate the corresponding dew point. The system then behaves as if it had a “dew point sensor”. Software can use data from physical and virtual sensors to take corrective action such as controlling heating to prevent the formation of condensation in areas at risk.

Other examples of virtual sensors are the estimation of air change rate via the physical measurement of CO₂ decay rate; the calculation of thermal comfort indices based on physical measurement of temperature, humidity and air movement; and the estimation of the levels of fine particulate matter and volatile organic compounds within a building from physical measurement of levels in the outdoor air combined with knowledge of building occupancy and its heating, ventilation, and air conditioning performance.

The future of digital twins

The director of a company supplying digital twin platforms which integrate building data gave his views on the immediate future of digital twins in a recent article (Twinview, 2026).

Sectors such as higher education, healthcare, social housing or large commercial real estate portfolios were thought most likely to show activity, having “all the drivers in play, such as ageing estates, constrained budgets, regulatory pressure, high occupant expectations and a strong need for performance transparency.” Immediate concerns included centralising the data, integrating systems, and “making sure the digital twin reflects the … operational reality” of the building.

A good digital twin in 2026 “should feel less like a model and more like an operating layer.” The owner should be able get prompt answers on “what’s not working, what’s wasting energy, what needs attention today and what’s going to become a problem next week.” Projects in the company’s portfolio show public sector, university, commercial and large residential apartment developments.

While digital twin technology could well provide advantages in individual domestic properties in areas such as energy saving and planned maintenance, the costs involved may be too high at present. However, technology costs can decrease, and with time the approach may become more affordable and useful in small properties.

References

BE-ST, 2025, Revolutionising the approach to retrofit & building upgrades, online, accessed 27 January 2026

https://www.be-st.build/alchemai

CES, 2025, How much to build a Digital Twin? The Consulting Engineer Survivor, online, accessed 28 January 2026

https://www.consultengsurvivor.com/cost-to-build-a-digital-twin

CTO, 2025, Digital Twins: Definition, Uses and Implementation Challenges, CTO Academy, online, accessed 26 January 2026

https://cto.academy/digital-twins-definition-uses-challenges-solutions/#

HUBBPRO, 2025, Unlocking the Future of UK Housing: Digital Twins – Micro and Macro Insights, 2025, online, accessed 27 January 2026

https://hubb.pro/blog/future-of-uk-housing-digital-twins/

MD, 2024, Top 10: Uses Of Digital Twins, Manufacturing Digital, online, accessed 26 January 2026

https://manufacturingdigital.com/articles/top-10-uses-for-digital-twins

NASA, 2021, Digital Twins and Living Models at NASA, NTRS, online, accessed 24 January 2026

https://ntrs.nasa.gov/citations/20210023699

Nemetschek, 2024, Digital Twins, online, accessed 27 January 2026

https://www.nemetschek.com/en/topics/digital-twins

NIST, 2024, Economics of Digital Twins, National Institute of Standards and Technology, online, accessed 27 January 2026

https://nvlpubs.nist.gov/nistpubs/ams/NIST.AMS.100-61.pdf

Twinview 2026, What Do Digital Twins Hold for 2026: From Visualisation to Smart Building Operations, online, accessed 27 January 2026

https://www.twinview.com/insights/what-do-digital-twins-hold-for-2026-from-visualisation-to-smart-building-operations


 

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