AI Lab : A Case Study on the Integration of AI into Building Design Workflows

Fagan, Des (2025) AI Lab : A Case Study on the Integration of AI into Building Design Workflows. In: BIM In Leicester 2025, 2025-02-05 - 2025-02-05, De Montford University.

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Abstract

The AI:Lab - Artificial Intelligence for Low Carbon Building (Des Fagan – Principal Investigator), a funded research project incorporating computer scientists, engineers and architects concluded in early 2025, after a year of research and consultation activities on the potential of integrating AI workflows into the design process, specifically BIM software. The Ai:Lab asked: how can processes of Artificial Intelligence (AI) target the reduction of carbon expenditure in the design and construction of buildings, and what role do architects, engineers, our students, and the public have in the process of de-carbonisation using new tools of AI integrated with the design process? Working with Grimshaw Architects, and with a focus on the new Eden Project in Morecambe Bay, our key objective was to establish the Ai:Lab as a vehicle to recognise the cross-disciplinary demands and opportunities of AI integrated with BIM, to capture these at an early stage, and produce impactful research in communities and across the construction sector. The Lab ran during 2024, concluding with a symposium and exhibition on the use of AI in designing low carbon buildings. Four key areas of focus were established: (1) LLM Workflow Integration with BIM for the Zero Carbon Standard (2) Local Knowledge LLM Workflow Integration (3) 3D Shape Generation Using Parsed Image Data (4) Structural Shell Deflection Maps Generated with Linear Regression Models. This talk will explore the impact of the Ai:Lab, evaluating its outcomes, exploring responses from construction professionals, students, and the public to the prospect of an AI-augmented low carbon-first environment.

Item Type:

Contribution to Conference (Speech)

Journal or Publication Title:

BIM In Leicester 2025

Additional Information:

Head of Architecture at Lancaster, my field of research interest is in Optimisation and Deep Learning (Artificial Intelligence) for Decision Support Systems in design. I am particularly interested in the impact that Machine Learning will have on design processes and the regulatory and policy implications for the RIBA and ARB. My roles in the field of AI and Architecture include member of the Expert Advisory Group on Data and AI in Practice (RIBA), and Lead of the Working Group on AI in Architectural Education (SCOSA) where I lead a network of industry partners including AutoDesk, Google and OpenAI, to guide the future integration of AI across UK practices and teaching acrossall 65 Schools of Architecture. Prior to working in academia, I worked on several international award‐winning projects, including as Project Architect for the London Olympic Village 2012 and for Glasgow Transport Museum at Zaha Hadid Architects, winner of European Museum of the Year 2013. I am currently working on a UKRI funded project: AILab: Artificial Intelligence in Low Carbon Building with Eden Project and Grimshaw Architects, to realise the advantages of Machine Learning for low carbon construction of Eden Morecambe

Uncontrolled Keywords:

Research Output Funding/yes_internally_funded

Subjects:

?? artificial intelligenceaisustainabilitylow carbonoptimisationeden projectgrimshawarchitecturellm workflowsurrogate modelingyes - internally funded ??

Departments:

Faculty of Arts & Social Sciences > Lancaster Institute for the Contemporary Arts

ID Code:

227851

Deposited By:

ep_importer_pure

Deposited On:

28 Feb 2025 13:55

Refereed?:

Published?:

Published

Last Modified:

26 Mar 2025 00:41

URI:

https://eprints.lancs.ac.uk/id/eprint/227851