Personal comfort models based on a 6-month experiment using environmental parameters and data from wearables.

ABSTRACT: Personal thermal comfort models are a paradigm shift in predicting how building occupants perceive their thermal environment. Previous work has critical limitations related to the length of the data collected and the diversity of spaces. This paper outlines a longitudinal field study comprising 20 participants who answered Right-Here-Right-Now surveys using a smartwatch for 180 days. We collected more than 1080 field-based surveys per participant. Surveys were matched with environmental and physiological measured variables collected indoors in their homes and offices. We then trained and tested seven machine learning models per participant to predict their thermal preferences. Participants indicated 58% of the time to want no change in their thermal environment despite completing 75% of th

SUBMITTER: Tartarini F 

PROVIDER: S-EPMC9827859 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature