• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.140-145
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• 2022

In an advanced modern society, among air pollutants caused by urban industrialization and public transportation, fine dust flows into indoors from the outdoors. The fine dust meter used indoors provides limited information and measures the pollution level differently, so there is a problem that users cannot monitor and monitor the data they want. To solve this problem, in this paper, indoor air quality data fine dust and ultra-fine dust (PM1.0, PM2.5, PM10), VOC (Volatile Organic Compounds) and PIR (Passive Infrared Sensor) are used to measure fine dust. and a monitoring system were designed and implemented. We propose a fine dust meter and monitoring system that is installed in a designated area to measure fine dust in real time, collects, stores, and visualizes data through App Engine of Google Cloud Platform and provides it to users.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.91-92
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• 2015

현재 실외 대기 중 미세먼지농도는 한국환경공단으로부터 지역별 실시간 정보를 받아볼 수 있다. 하지만 일반가정이나 사무실, 개개인이 있는 실내의 지속적인 공기상태는 사용자가 직접 미세먼지를 측정하는 기기를 사용하여 측정해야 만이 확인이 가능하기 때문에 쉽게 알기가 어렵다. 언제 어디서든 손쉽게 공기오염도를 측정 할 수 있으며 오염도가 심한 수준일 경우 사용자가 즉시 알 수 있다면 이를 조금 더 손쉽게 예방하고 대처할 수 있을 것이다. 본 논문에서는 공기의 질을 측정 할 수 있는 휴대용 측정기와 개인이나 가정의 실내 공기의 질을 손쉽게 측정할 수 있는 실내측정기를 개발하여 사용자가 실시간으로 측정된 정보를 받을 수 있도록 하는 시스템의 개발내용에 대해 기술한다.

• Air Cleaning Technology
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• v.33 no.3
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• pp.44-53
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• 2020

• Journal of Korea Entertainment Industry Association
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• v.13 no.6
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• pp.69-77
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• 2019

Among the many factors that threaten the improvement of public health and quality of life, the proportion of fine dust is not so small, and the kinds and causes of the dust are also diversified. However, the domestic measuring instrument is in the initial stage and the certification system is insignificant. Recognizing the threat of fine dust for a long time, the United States has established a protocol of measurement standards and measurement methods and applied the developed fine dust measuring device authentication system. Through this system, the United States is leading the world's fine dust industry, technology and market. The EPA, FRM and FEM of the fine dust-related protocol were analyzed to reduce the harmful effects of repeated fine dust every year. In addition, light scattering method and spectroscopy method which can measure in real time by measuring method were examined, and the types and characteristics of fine dust measuring instrument of international certification level were analyzed. Finally, development and service plan of the domestic fine dust measuring instrument are presented.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.218-236
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• 2023

This study attempted to analyze the environmental equity of fine dust(PM₁₀) in Daegu using MGWR(Multi-scale Geographically Weighted Regression) and KT(Korea Telecom Corporation) sensor data. Existing national monitoring network data for measuring fine dust are collected at a small number of ground-based stations that are sparsely distributed in a large area. To complement these drawbacks, KT sensor data with a large number of IoT(Internet of Things) stations densely distributed were used in this study. The MGWR model was used to deal with spatial heterogeneity and multi-scale contextual effects in the spatial relationships between fine dust concentration and socioeconomic variables. Results indicate that there existed an environmental inequity by land value and foreigner ratio in the spatial distribution of fine dust in Daegu metropolitan city. Also, the MGWR model showed better the explanatory power than Ordinary Least Square(OLS) and Geographically Weighted Regression(GWR) models in explaining the spatial relationships between the concentration of fine dust and socioeconomic variables. This study demonstrated the potential of KT sensor data as a supplement to the existing national monitoring network data for measuring fine dust.

• Journal of Science Education
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• v.44 no.2
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• pp.183-196
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• 2020

This study explores the effects of STEAM program using Arduino on preservice science teachers toward their STEAM core competencies. The STEAM program using Arduino consists of four stages: presentation of situation, creative design, emotional touch, and evaluation. The preservice science teachers learned the theoretical backgrounds of STEAM and Arduino. Then, they were given the chance to think about an environmental issue, which is fine dust. The preservice teachers designed an air cleaner and a fine dust measuring instrument using Arduino. The preservice science teachers also produced the air cleaner and the measuring instrument using Arduino. They measured the level of fine dust in the classroom before and after the use of the air cleaner. That is, the preservice teachers experienced each stage of STEAM: seriousness of fine dust, design and production of the measuring instrument of fine dust and air cleaner, and evaluation of the effectiveness of air cleaner. Further, they reflected on their experiences of STEAM program using Arduino. The results indicate that these preservice science teachers statistically improved communication competency, problem-solving competency, gathering information competency, logical analytical thinking competency, and creativity competency. However, there were no statistical improvements on teamwork competency and self-development competency. This study suggests that experiencing STEAM program using Arduino is valuable for the preservice science teachers to develop STEAM core competencies and further implement STEAM program their science classes in the future.

• The Journal of Bigdata
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• v.6 no.2
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• pp.39-49
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• 2021

Recently, large and diverse weather data are being collected by sensors from various sources. Efforts to predict the concentration of fine dust through machine learning are being made everywhere, and this study intends to compare PM10 and PM2.5 prediction models using data from 840 outdoor air meters installed throughout the city. Information can be provided in real time by predicting the concentration of fine dust after 5 minutes, and can be the basis for model development after 10 minutes, 30 minutes, and 1 hour. Data preprocessing was performed, such as noise removal and missing value replacement, and a derived variable that considers temporal and spatial variables was created. The parameters of the model were selected through the response surface method. XGBoost, Random Forest, and Deep Learning (Multilayer Perceptron) are used as predictive models to check the difference between fine dust concentration and predicted values, and to compare the performance between models.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.373-376
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• 2022

미세먼지 수집을 위하여 필요한 위치 선정 방안과 위치 선정시 중요한 바람길분석, 수요조사, 유동인구, 교통량 등의 중요 기준을 반영하여 최종 선정하여야 하며, 이에 따라 설치된 측정기로부터 데이터 수집을 위해 지역적, 환경적, 지형적 요소를 감안하여 수집 항목을 결정하여야 한다. 데이터 수집시 실시간 또는 배치(Batch)로 할 것인지 여부를 결정하여야 하며, 이 보고서에서는 실시간으로 데이터 수집하는 경우를 설명하였다. 데이터 수집시 정확도를 높이기 위해 결측값, 이상값인 전처리 단계를 거쳐서 분석과 Modeling 구축을 통하여 정확도가 높은 알고리즘을 선정하여야한다. 정확도가 높은 알고리즘은 검증용 데이터 셋으로 적합성을 검증하여, 측정기 설치 위치의 적합성, 데이터 수집의 적합성, Modeling 구축 및 평가가 적합함을 지표로서 제시하여 적합성 검증을 하고자 한다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.6
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• pp.119-128
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• 2020

An ultrasonic multiple scattering simulation using cross-section of fine dust particles were proposed. These days, along with awareness of air pollution, social interest in fine dust is increasing. In the construction field, awareness of fine dust is increasing, and research on preparing various countermeasures is underway. The light scattering method fine dust meter currently in use is affected by environmental factors such as relative humidity, and reliability problems in terms of accuracy are continuously reported. However, the transmission of ultrasonic waves can directly reflect the physical change of the medium based on the mechanical wave. Using these advantages of ultrasonic waves, fine dust measurement simulation was performed using the scattering cross section and ultrasonic multiple scattering theory. The shape data of the fine dust particles were collected using a SEM (Scanning Electron Microscope), and a cross-section according to the fine dust particles was derived through numerical analysis. As a result of signal processing, the error for the number density corresponding to each cross-section is minimum 19, maximum 3455.

• Journal of Environmental Impact Assessment
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• v.27 no.4
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• pp.378-393
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• 2018

As atmospheric fine dust problems in Korea become more serious, there are growing needs to find the concentration of fine particles in indoor and outdoor areas and there are increasing demands for sensor-based portable monitoring devices capable of measuring fine dust concentrations instantly. The low-cost portable monitoring devices have been widely manufactured and used without the prescribed certification standards which would cause unnecessary confusion to the concerned public. To evaluate the reliability those devices and to improve their usability, following studies were conducted in this work; 1) The comparisons between sensor-based devices and comparison with more accurate devices were performed. 2) Several experiments were conducted to understand usefulness of the portable monitoring devices. As results, the absolute concentration levels need to be adjusted due to insensitivity of the tiny light scattering sensors in the portable devices, but their linearity and reproducibility seem to be acceptable. By using those monitoring devices, users are expected to have benefits of recognizing the changes of concentration more quickly and could help preventing themselves from the adverse health impacts.