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https://doi.org/10.1088/1742-6596/1343/1/012145
Title: | Is your clock-face cozie? A smartwatch methodology for the in-situ collection of occupant comfort data | Authors: | Jayathissa, Prageeth Quintana, Matias Sood, Tapeesh Nazarian, Negin Miller, Clayton |
Keywords: | Science & Technology Technology Construction & Building Technology Green & Sustainable Science & Technology Energy & Fuels Science & Technology - Other Topics |
Issue Date: | 1-Jan-2019 | Publisher: | IOP PUBLISHING LTD | Citation: | Jayathissa, Prageeth, Quintana, Matias, Sood, Tapeesh, Nazarian, Negin, Miller, Clayton (2019-01-01). Is your clock-face cozie? A smartwatch methodology for the in-situ collection of occupant comfort data. CLIMATE RESILIENT CITIES - ENERGY EFFICIENCY & RENEWABLES IN THE DIGITAL ERA (CISBAT 2019) 1343 (1). ScholarBank@NUS Repository. https://doi.org/10.1088/1742-6596/1343/1/012145 | Abstract: | Labelled human comfort data can be a valuable resource in optimising the built environment, and improving the wellbeing of individual occupants. The acquisition of labelled data however remains a challenge. This paper presents a methodology for the collection of in-situ occupant feedback data using a Fitbit smartwatch. The clock-face application cozie can be downloaded free-of-charge on the Fitbit store and tailored to fit a range of occupant comfort related experiments. In the initial trial of the app, fifteen users were given a smartwatch for one month and were prompted to give feedback on their thermal preferences. In one month, with minimal administrative overhead, 1460 labelled responses were collected. This paper demonstrates how these large data sets of human feedback can be analysed to reveal a range of results from building anomalies, occupant behaviour, occupant personality clustering, and general feedback related to the building. The paper also discusses limitations in the approach and the next phase of design of the platform. | Source Title: | CLIMATE RESILIENT CITIES - ENERGY EFFICIENCY & RENEWABLES IN THE DIGITAL ERA (CISBAT 2019) | URI: | https://scholarbank.nus.edu.sg/handle/10635/189386 | ISSN: | 17426588 17426596 |
DOI: | 10.1088/1742-6596/1343/1/012145 |
Appears in Collections: | Staff Publications Elements Students Publications |
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