From Fixed-purpose to Adaptive Intelligence: Pathway to General-purpose Intelligence for Buildings

Xiang Xie1, Mohamad Kassem1, Joao Patacas1, Philip James1, Edlira Vakaj2
1 School of Engineering, Newcastle University, UK
2 Faculty of Computing, Engineering and the Built Environment, Birmingham City University, UK
DOI: 10.35490/EC3.2025.229
Abstract: Buildings own diverse datasets, including geometric, product, logistic, real-time monitoring, regulatory, and occupant feedback data. However, challenges such as data scarcity, insufficient labelling, and the complexity of multimodal data limit conventional AI’s ability to provide accurate, scalable and content-aware insights, often confining its application to specific buildings and time. General-Purpose Artificial Intelligence (GPAI) offers the transformative potential to maximise the value of data. Early research explores adaptive AI, meta-knowledge transfer, synthetic data, and foundation models to support generalisation across tasks. This paper examines how these developments position GPAI as a step toward general-purpose intelligence in buildings.

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