Digital twins – building sustainable and affordable homes

Summary

London faces a severe housing crisis. In 2018, The London Housing Strategy was designed to provide affordable, high–quality, and environmentally sustainable homes while integrating community needs. Still, hundreds of construction projects have been put on hold due to financial constraints, shortages of skilled labour, and ongoing supply chain issues.

To tackle these issues, digital twin technology emerges as a transformative solution. As virtual real–time replicas of physical environments, these new tools allow building cheaper, faster, and safer homes for communities by:

1. Optimising resource allocation
2. Improving sustainability and adaptability
3. Strengthening stakeholder collaboration

AL’MA’s Bio Garden Homes development in Mayotte (France), prototyped via its digital twin “Better Homes 4 All”, is a powerful case study. It demonstrates that social initiatives may benefit from advanced digital tools and provides a reference for policymakers to transform construction practices and improve sustainability.

This briefing will be of interest to all councillors and officers concerned with affordable housing who wish to prioritise innovation in their local public–private partnerships.

Background

London has been facing an unprecedented housing crisis as it fails to provide enough suitable homes to meet the needs of its growing population. When housing supply falls short of demand, prices rise, making housing unaffordable for many residents. Homelessness has reached record levels, with more than one in every 50 Londoners living in temporary accommodation, costing boroughs £4m a day. There is also overwhelming demand for social housing: waiting lists have reached a 10-year high, with 336,366 households registered since 2024.

To respond to the housing shortage, the Mayor of London had formulated The London Housing Strategy in 2018, which seeks to provide well-designed, high- quality, and environmentally sustainable housing while integrating community needs. Yet hundreds of construction projects have been put on hold due to financial constraints, shortages of skilled labour, and ongoing supply chain issues. Traditional construction methods are proving too slow and costly to meet the urgent demand.

AI might offer a way to start addressing these challenges, with digital twins, a construction tool that has the potential to revolutionise social housing by enabling projects to be built cheaper, faster, and safer homes with a focus on community and sustainability.

What are digital twins?

Digital Twin of London, by Anstey Home

Digital twins are data-driven virtual replicas of real-world systems. They replicate the structure, context, and citizens’ behaviours of real communities, and are updated in real-time with data from sensors, operational logs, and imaging.

The key benefit of digital twins is their bi-directional flow of information: data from the real word continuously informs the digital model, and insights generated virtuallydrive optimal interventions in the physical system. These flows are mediated both by human interaction and algorithms.

Figure 1: Digital Twins in the Built Environment

Construction Placements

How can digital twins support affordable housing?

Before committing to a fixed model, digital twins allow planners to simulate and predict how various prototypes interact across environmental conditions. Compared to traditional construction approaches, they offer the potential to deliver faster, safer, and more affordable housing by:

1. Optimising resource allocation: The system helps expedite construction timelines while reducing waste and costs through higher design precision, automated issue detection and supply chain optimisation (economies of scale and scope, no shortages, better sourcing practices).
2. Sustainability and adaptability: Predictive analytics forecast material evolution over time, and helps make decision that increase resilience against changing climate conditions (for e.g., heat, humidity).
3. Improved stakeholder collaboration: A unified digital representation centralises construction data, sharing insights from architects, policymakers, and community members, to improve decision making and support networks.

This modern construction tool has been adopted in the construction of a new eco-neighbourhood in Mayotte, as discussed below:

Case study: Insight from the AL’MA Bio Garden Homes in Mayotte

AL’MA’s Bio Garden Homes aims to deliver 240 sustainable homes to the Chiconi commune in Mayotte as part of a broader plan to build 5,000 houses. AL’MA is a subsidiary of Groupe Action Logement, dedicated to creating affordable housing that meets the needs of employees, businesses, and the local community. The group’s objective is to reduce greenhouse gas emissions related to the maintenance of its buildings by 55% by 2030.

Digital Twin of AL’MA’s Bio Garden Homes: Housing

At the heart of the project is the “Better Homes 4 All” digital twin, which continuously aggregates data from a network of IoT sensors. The project uses a variety of low-carbon building systems, and other key parameters include material quality, energy consumption, and local environmental conditions to run simulations, allowing “the project team to make proactive adjustments in the prototyping stage”, explains Dr. Delphine Sangodeyi, Director of AL’MA Action Logement.

AL’MA’s Bio Garden Homes in Mayotte demonstrates how even in challenging environments, innovators can seize opportunities if they can prove the business case. As Dr. Sangodeyi shared, this is a “long-term investment, necessary to sustainably scale all projects up”. Here’s how they look at it:

Optimising resource allocation

By supporting the adoption of digital twins, policymakers can drive cost efficiency and deliver significantly higher-quality housing to their constituents.

“Digital twins were a strategic investment for the group”, shared Dr. Sangodeyi. She recalls, “We were frustrated with poor quality materials and realised that investing in these technologies would yield significant long-term economic benefits.” This commitment addressed longstanding challenges in construction quality, notably by eliminating design errors which can significantly impact costs.

She adds: “Traditional design processes used to involve a lot of different actors, iterations, and revisions.” Such variability not only slowed progress but also increased the risk of inconsistencies. By integrating digital twin technology, AL’MA has optimised the design process. Architects can now generate a wide range of design options based on parameters like budget constraints, environmental conditions, and spatial limitations. Running simulations during the prototyping phase allows us to assess how each design would perform in real-world conditions and to vet, improve or discard these options quickly. This also helps avoid costly rework at later stages.

Although this approach may limit “creative variability, as models follow a framework of set materials,” it enables greater consistency, faster decision-making, and higher construction quality. Importantly, relying on a standardised set of materials allows for bulk purchasing, thereby reaping economies of scale and minimising the risk of shipping delays, particularly in remote locations like Mayotte. Finally, material waste is significantly reduced, positioning digital twins as a sustainable strategy, in line with the Group’s commitment to protect communities from the impact of climate change.

Improving sustainability and adaptability

By supporting the adoption of digital twins, policymakers can ensure safer housing for their constituents and better prepare communities for future climate variability.

Reflecting on the devastating consequences of Cyclone Chido, Dr. Sangodeyi laments that digital twin systems “would have allowed to forecast how construction materials respond under harsh weather conditions,” providing a powerful predictive tool to select safer and more resilient materials.

Environmental data is a critical component in the predictive analytics of affordable housing. Advanced models can confront data on building performance, occupant behaviour, and weather patterns to forecast the long-term performance and durability of construction materials across environments. As climate change increasingly threatens urban areas, with challenges such as deteriorating air quality and flood risks, these models help identify safer sites for housing development and recommend design changes that improve structural resilience.

Strengthening stakeholder collaboration

By supporting the adoption of digital twins, policymakers can ensure that local communities are involved and actively engaged in networks focused on social development, ultimately delivering housing that truly meets their needs.

Community engagement must remain at the centre of the design process. Cities are dynamic, socio-physical systems shaped by the interactions of their inhabitants. Dr. Sangodeyi explains that AL’MA remains highly respectful and conscious of “local traditional practices and cultural values.” The Bio Garden Homes incorporates spaces for parks, sports, and social gatherings that reflect the region’s strong collectivist culture and the importance of communal celebrations. Additionally, Dr. Sangodeyi notes that AL’MA “ordered multiple prototypes that will now be tested in real-life conditions” to validate the system’s predictions and incorporate the population’s feedback to validate the best solutions.

Digital Twin of AL’MA’s Bio Garden Homes: Communal Spaces

Dr. Sangodeyi also stresses how robust coalition networks are required to achieve success. “AL’MA has built significant partnerships over the years with a diverse range of stakeholders, from start-ups offering digital solutions to multinational companies providing know-how and resources.” This includes contributions from Saint Gobain, SingularityNET and Leonard, the innovation platform of Vinci Group. Governmental funding plays an integral role as well, encouraging the group to integrate local businesses in the project ecosystem and to seek public-private synergies to gain high population approval.

What’s next? The path to affordable and sustainable local housing

In the context of a worsening housing crisis, London must urgently explore alternatives to traditional urban planning to reach its sustainable and affordable housing objectives. Digital twins are an investment that have the potential to enable The London Housing Strategy, as they optimise resource usage, improve construction quality and speed, and reduce waste, while keeping communities at the centre.

To fully realise their potential, digital twins must be tailored to meet the specific challenges of London. At a policy level, this requires several key considerations:

• Future demand projections: Digital twin models must integrate data on local climate conditions and on sustainable building materials available locally.
• Community involvement: the identity and needs of future residents is a key factor of adoption and satisfaction, navigating heritage and new usages.
• Innovation partnerships: Successful implementation of digital twins requires collaboration with an ecosystem of local partners.
• Regulatory and planning constraints: Digital twin systems must adhere to local safety, privacy standards, building codes, and accessibility requirements.

With this in mind, public-private partnerships may seize the opportunity to drive a transformative shift in urban planning, and deliver safer, resilient and affordable housing.