• ISSN 2319-6378 (Online)Volume 14, Issue 2 • February 28, 2026
Thermal Comfort Prediction in Classrooms Using Low-Cost Multi-Sensor Data
Open access • Peer reviewed • CC BY-NC-SA 4.0
Eliana Duarte (Author) ORCID
Environmental MonitoringMachine LearningBuilding Systems
Abstract
The author models classroom thermal comfort from temperature, humidity, and airflow measurements captured by student-installed sensors. The resulting predictor aligned well with occupant surveys and supported practical ventilation adjustments.
Citation
Eliana Duarte (2026). Thermal Comfort Prediction in Classrooms Using Low-Cost Multi-Sensor Data. Journal of Young Scientists & Engineers, 14(2). https://doi.org/10.35940/jyse.AIML.2026.140411
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Access
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