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http://dx.doi.org/10.5668/JEHS.2018.44.5.421

Development of an IAQ Index for Indoor Garden Based IoT Applications for Residents' Health Management  

Lee, Jeong-Hun (Life & Industry Environmental R&D Center in Pyeongtaek University)
An, Sun-Min (Life & Industry Environmental R&D Center in Pyeongtaek University)
Kwak, Min-Jung (Department of Data Information and Statistics in Pyeongtaek University)
Kim, Kwang Jin (Urban Agriculture Research Division in National Institute of Horticulture & Herbal Science)
Kim, Ho-Hyun (Life & Industry Environmental R&D Center in Pyeongtaek University)
Publication Information
Journal of Environmental Health Sciences / v.44, no.5, 2018 , pp. 421-432 More about this Journal
Abstract
Objectives: In this study, we started to develop an indoor garden integrated IoT solution based on IAQ (indoor air quality) and interconnection with an environmental database for smart management of indoor gardens. The purpose of this study was to develop and apply an integrated solution for customized air purification from an indoor garden through big data analysis using IoT technology. Methods: An IoT-based IAQ monitoring system was established in three households within a new apartment building. Based on real-time and long-term data collected, $PM_{2.5}$, $CO_2$, temperature, and humidity changes were compared to those of indoor garden applications and the analyzed results were indexed. Results As a result of the installation, all three households had no results exceeding the standard for indoor air pollution on average $PM_{2.5}$ and $CO_2$ indices. In the case of indoor garden installation, the IAQ index increased to the "Good" section after the installation, and readings in the "Bad" section shown before the installation disappeared. The comfort index also did not dip into the "Uncomfortable" section, where it had been preinstallation, and significantly lowered the average score from "Uncomfortable for sensitive groups" to "Good". Overall, the IAQ composite index for the generation of installations decreased the "Good" interval, but "Bad" did not appear. Conclusions In this study on developing an integrated solution for IAQ based on IoT indoor gardens, big data was analyzed to determine IAQ and comfort indexes and an IAQ composite index. Through this process, it became understood that it is necessary to monitor IAQ based on IoT.
Keywords
Indoor garden; health management; IAQ; index; newly-built apartment;
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