Open AccessIs your clock-face cozie? A smartwatch methodology for the in-situ collection of occupant comfort data
Author(s) -
Prageeth Jayathissa,
Matias Quintana,
Tapeesh Sood,
Negin Nazarian,
Clayton Miller
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1343/1/012145
Subject(s) - smartwatch , computer science , human–computer interaction , overhead (engineering) , data collection , crowdsourcing , cluster analysis , range (aeronautics) , wearable computer , embedded system , world wide web , engineering , artificial intelligence , operating system , aerospace engineering , statistics , mathematics
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.