The objective of this study is to analyze the indoor air quality of multi-use facilities using an IoT-based monitoring and control system. Thise study aims to identify effective management strategies and propose policy improvements. This research focused on 50 multi-use facilities, including daycare centers, medical centers, and libraries. Data on PM10, PM2.5, CO2, temperature, and humidity were collected 24 hours a day from June 2019 to April 2020. The analysis included variations in indoor air quality by season, hour, and day of the week (including both weekdays and weekends). Additionally, ways to utilize IoT monitoring systems using big data were propsed. The reliability analysis of the IoT monitoring network showed an accuracy of 81.0% for PM10 and 76.1% for PM2.5. Indoor air quality varied significantly by season, with higher particulate matter levels in winter and spring, and slightly higher levels on weekends compared to weekdays. There was a positive correlation found between outdoor and indoor pollutant levels. Indoor air quality management in multi-use facilities requires season-specific strategies, particularly during the winter and spring. Furhtermore, enhanced management is necessary during weekends due to higher pollutant levels.

1. 서 론
2. 연구 방법
    2.1 연구 대상 및 기간
    2.2 다중이용시설 실내공기질 특성 분석
    2.3 빅데이터 분석을 통한 다중이용시설 실내공기질 개선 정책 활용 제안
3. 결과 및 고찰
    3.1 IoT 자동측정망 데이터 신뢰도 분석
    3.2 다중이용시설 유형별 실내공기질 특성
    3.3 외기의 실내공기질 영향 여부 회귀 분석
4. 결 론
감사의 글
Reference

• 김호현(서경대학교 나노화학생명공학과,생활 및 산업 환경연구소) | Ho Hyun Kim (Department of Nano-Chemical Biological and Environmental Engineering, Seokyeong University) Corresponding author