The indoor environment has become the primary habitat. According to the U.S. Environmental Protection Agency, the average American spends 93% of their life indoors, with 87% spent inside buildings and 6% in automobiles. There is a pressing need to design and renovate the built environment to better serve human occupants. This requires a multidisciplinary approach, and, in recent years, due to the advances in devices, computational speed achievable on small surface chips, and Internet of Things (IoT) platforms, artificial intelligence (AI) has come to play a crucial role in making effective use of these technologies by enhancing the modeling and control of buildings in a way that shifts the focus from the building to the occupant. The goal of this paper is to explore state-of-the-art AI research in the domain of healthy buildings. We do so by formulating seven questions focusing on three themes. First, we explore how new data sources and data platforms have enabled AI to be adopted for the paradigm of healthy buildings, including the use of IoT technologies and the associated opportunities and challenges arising from a wide range of data sources. Second, we investigate AI-informed approaches for healthy building design and control, encompassing physical building models as well as human behavioral models representing occupants. Finally, we reflect on the building certification process, and examine examples from academic research labs and real-world constructions to understand the current state and existing use cases. The study establishes a foundation to understand the role of AI in healthy buildings and it provides insights for future research directions.
Journal article
Understanding the role of artificial intelligence in improving human well-being within the built environment
Building simulation, v 18, pp 1727-1742
26 Jul 2025
Featured in Collection : UN Sustainable Development Goals @ Drexel
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Details
- Title
- Understanding the role of artificial intelligence in improving human well-being within the built environment
- Creators
- Asra Aghaei - Arizona State UniversityGiulia Pedrielli (Corresponding Author) - Arizona State UniversityTeresa Wu - Arizona State UniversityZheng O’Neill - Texas A&M UniversityBurçin Becerik-Gerber - University of Southern CaliforniaSimi Hoque - Drexel UniversityJin Wen - Drexel University
- Publication Details
- Building simulation, v 18, pp 1727-1742
- Publisher
- Springer Nature
- Number of pages
- 16
- Grant note
- National Science Foundation: 1931226, 2009754, 1931238, 1931254
The research presented in this work was partially supported by the National Science Foundation under Grants No. 1931226, 2009754, 1931238, and 1931254. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:001536012200001
- Scopus ID
- 2-s2.0-105011641948
- Other Identifier
- 991022068078304721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Construction & Building Technology
- Thermodynamics