Human-Centric Artificial Intelligence of Things–Based Indoor Environment Quality Modeling Framework for Supporting Student Well-Being in Educational Facilities
Publication: Journal of Computing in Civil Engineering
Volume 38, Issue 2
Abstract
Maintaining the quality of indoor environments in educational facilities is crucial for student comfort, health, well-being, and students’ learning performance. Current indoor environment maintenance practices and building systems for educational facility spaces often fail to include feedback from students and exhibit limited adaptability to their needs. To address this problem, this paper introduces a novel artificial intelligence of things (AIoT)-based framework to predict multidimensional indoor environment quality (IEQ) conditions. The proposed framework integrates internet of things (IoT) systems with deep learning algorithms to systematically incorporate multidimensional IEQ data and multimodal feedback from occupants. By collecting, fusing, and analyzing real-time IEQ and occupant feedback data, the proposed framework predicts the future IEQ condition based on current conditions. This framework yields insights into the IEQ conditions and their potential impacts on student well-being, thereby facilitating the future development of climate-adaptive, data-driven, and human-centric educational facilities. This framework was deployed, validated, and tested in selected educational facilities at the Virginia Tech Blacksburg campus, with encouraging results.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request, including the IEQ data, deidentified occupant feedback data, and the models and code of the proposed IEQ Framework.
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Journal of Computing in Civil Engineering
Volume 38 • Issue 2 • March 2024
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© 2024 American Society of Civil Engineers.
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Received: Jul 30, 2023
Accepted: Nov 27, 2023
Published online: Jan 3, 2024
Published in print: Mar 1, 2024
Discussion open until: Jun 3, 2024
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