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基于物联网的室内花园的室内空气质量管理评估。

Evaluation of IAQ Management Using an IoT-Based Indoor Garden.

机构信息

Department of Information, Communication and Technology Convergence, ICT Environment Convergence, Pyeongtaek University, 3825 Seodong-daero, Pyeongtaek-si, Gyeonggi-do 17869, Korea.

Department of Data Information and Statistics in Pyeongtaek University, 3825, Seodong-daero, Pyeongtaek-si, Gyeonggi-do 17869, Korea.

出版信息

Int J Environ Res Public Health. 2020 Mar 13;17(6):1867. doi: 10.3390/ijerph17061867.

Abstract

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, CO, 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 and CO, 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.

摘要

本研究旨在通过安装具有基于传感器的物联网 (IoT) 技术的室内花园来验证智能花园的有效性,该技术可以识别颗粒物等污染物。此外,本研究旨在利用数据和物联网技术引入用于定制室内空气清洁的室内花园。选择 2016 年完成的新公寓,并将其分为四个装有室内花园的家庭和四个没有室内花园的家庭。通过基于物联网的室内空气质量监测系统收集实时数据和 PM、CO、温度和湿度数据。此外,为了检验对居住者健康的影响,根据流行病学数据、流行率数据、当前维护和推荐标准分析结果,并作为指标进行呈现和评估。这些指标分为舒适度指数,反映温度和湿度;室内空气质量指数,反映 PM 和 CO;以及室内空气质量综合指数。室内空气质量指数分为五个等级,从“良好”到“危险”。使用 1 到 100 分的评分标准,其结果如下:“良好(0-20)”“中等(21-40)”“对敏感人群不健康(41-60)”“不良(61-80)”“危险(81-100)”。安装室内花园后,“良好”部分增加,“不良”部分减少。此外,舒适度指数分为“非常舒适”到“非常不适”五个等级。在舒适度指数中,安装室内花园后,“不适”部分减少,“舒适”部分增加。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/799c/7142759/20085de9d244/ijerph-17-01867-g001.jpg

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