Journal of Environmental Health Sciences (한국환경보건학회지)

Korean Society of Environmental Health (한국환경보건학회)
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Development of an IAQ Index for Indoor Garden Based IoT Applications for Residents' Health Management

실내거주자 건강 관리를 위한 IoT기반 실내정원용 IAQ지수 개발

  • 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)
  • 이정훈 (평택대학교 생활 및 산업 환경R&D 센터) ;
  • 안선민 (평택대학교 생활 및 산업 환경R&D 센터) ;
  • 곽민정 (평택대학교 데이터정보학과) ;
  • 김광진 (농촌진흥청 국립원예특작과학원 원예작물부 도시농업과) ;
  • 김호현 (평택대학교 생활 및 산업 환경R&D 센터)
  • Received : 2018.09.06
  • Accepted : 2018.09.20
  • Published : 2018.10.28
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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

References

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