Evaluation of IAQ Management Using an IoT-Based Indoor Garden

Bibliographic Data

ID15465700
AuthorsHo-Hyun Kim (0000-0003-1648-0611, Pyeongtaek University, corresponding author), Min-Jung Kwak (0000-0003-3188-4059, Department of Data Information and Statistics in Pyeongtaek University, 3825, Seodong-daero, Pyeongtaek-si 17869, Gyeonggi-do, Korea), Min‐Jung Kwak (0000-0002-3853-4716, Pyeongtaek University), Kwang Jin Kim (0000-0002-2549-9720), Kwang-Jin Kim (Urban Agriculture Research Division, National Institute of Horticulture and Herbal Science, 100, Nongsaengmyeong-ro, Iseo-myeon, Wanju-gun 55365, Jeollabuk-do, Korea), Yoon-Kyung Gwak (Pyeongtaek University), Jeong-Hun Lee (0000-0002-3309-0319, Pyeongtaek University), Ho-Hyeong Yang (0000-0003-0958-3161, Pyeongtaek University)
Year2020
Volume17
Issue6
Pages1867-1867
Publication date2020-03-13
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph17061867
PMID32183085
OpenAlexW3011633375
LanguageEN
Citations received2
References cited18

This study was designed to verify the effectiveness of smart gardens by improving indoor air quality (IAQ) through the installation of an indoor garden with sensor-based Internet-of-Things (IoT) technology that identifies pollutants such as particulate matter. In addition, the study aims to introduce indoor gardens for customized indoor air cleaning using the data and IoT technology. New apartments completed in 2016 were selected and divided into four households with indoor gardens installed and four households without indoor gardens. Real-time data and data on PM 2.5 , CO 2 , temperature, and humidity were collected through an IoT-based IAQ monitoring system. In addition, in order to examine the effects on the health of occupants, the results were analyzed based on epidemiological data, prevalence data, current maintenance, and recommendation criteria, and were presented and evaluated as indices. The indices were classified into a comfort index, which reflects the temperature and humidity, an IAQ index, which reflects PM 2.5 and CO 2 , and an IAQ composite index. The IAQ index was divided into five grades from "good" to "hazardous". Using a scale of 1 to 100 points, it was determined as follows: "good (0-20)", "moderate (21-40)", "unhealthy for sensitive group (41-60)", "bad (61-80)", "hazardous (81-100)". It showed an increase in the "good" section after installing the indoor garden, and the "bad" section decreased. Additionally, the comfort index was classified into five grades from "very comfortable" to "very uncomfortable". In the comfort index, the "uncomfortable" section decreased, and the "comfortable" section increased after the indoor garden was installed

Architectural engineering · Computer security · Environmental health · Geography · Index (typography · Indoor air quality · Internet of Things · Meteorology · Ventilation (architecture · World Wide Web · Air Quality and Health Impacts · Air Quality Monitoring and Forecasting · Computer Science · Engineering · Environmental Science · Medicine · Urban Green Space and Health · Environmental Engineering

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