Widiastuti, Ratih (2023) C3 - ARTIKEL & HASIL REVIEW (Toward Utilizing IoT Open Data Set to Identify the Room Thermal Comfort). Journal of Architectural Design and Urbanism, 5 (2). pp. 54-60. ISSN 2620-9810

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Abstract

Building sectors are responsible for 33% of global energy consumption and a one-third of
CO2 emission as buildings are expected to experience high performance to meet the standard of
occupant comforts such as lighting, cooling, and heating. Internet of Things (IoT) as one of the leading
developments in digital technologies led to the establishment of devices for improving the living style
of the occupants. To date, studies on integrating the mechanisms of IoT to identify room thermal
comfort are very scarce. Therefore, the aim of this study was to discuss the room thermal comfort with
respect to room temperature and relative humidity. Three activities (read, write, and sit) were adopted.
The value of air speed, metabolic rate, and clothing insulation was assumed constant. The analysis
was conducted according to Fanger method and ASHRAE standard 55. Center for the Built
Environment (CBE) Thermal Comfort Tool was used to calculate the Predicted Mean Vote (PMV)
values. Results from data collection indicated the average room temperature was at ideal condition at
21.2°C with relative humidity 44.9%. Further calculation showed the average PMV values of each
activity were -2.3 (read), -2.0 (write), and -1.4 (sit). Compared to the room climate data set, sitting
performed the closest thermal comfort scale to the neutral. It means light activities with lower
metabolic rate should be conducted in the room with higher room temperature and relative humidity

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