This study was conducted as a part of the research for the “Development of Big Data Analysis Techniques and AI-based Integrated Support System for Energy-Environment Management.” We collected research results on characterization of distribution of fine dust and re-analyzed using meta-analysis techniques to build “big data” with high potential for school environments. The results of prior studies on the characteristics of fine dust concentration distribution in a school environment conducted in Korea were collected and re-analyzed the results using the metaanalysis technique. In this manner, the variables that could be used to derive the independent variables needed to produce the e-coding book prior to the big data collection, were first derived. The possibility of using the data as independent variables was then evaluated. In this study, three variables: “elementary school vs. middle school vs. high school,” “general classroom vs. special classroom,” and “new classroom vs. old classroom” were evaluated for their application as major classification variables with priority. The necessity of being derived as a major classification variable was examined by testing the difference in fine dust concentration distribution in the school environment by each variable case. Results showed that “elementary school vs. middle school vs high school” and “general classroom vs. special classroom” could be used as independent variables, while “new classroom vs. old classroom” was less likely to be used as an independent variable.

Abstract
1. 서 론
2. 연구방법
    2.1자료 수집
    2.2 메타분석
    2.3몬테카를로 모의실험
3. 결 과
    3.1초등학교, 중학교, 고등학교의 교실 내 미세먼지 농도분포 특성
    3.2일반교실 및 특수교실의 미세먼지 농도분포 특성
    3.3신축 및 기존 교실의 미세먼지 농도분포 특성
4. 고 찰
5. 결 론
References

• 이철민(서경대학교 화학생명공학과) | Cheol Min Lee (Department of Chemical & Biological Engineering, Seokyeong University) Corresponding author
• 김재현(서경대학교 컴퓨터공학과) | Jaehyun Kim (Department of Computer Engineering, Seokyeong University)