• 한국정보통신학회논문지
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• 제25권1호
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• pp.8-19
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• 2021

최근 산업화에 따른 대기오염 문제는 국가와 국민 모두에 큰 관심을 끌고 있다. 국내의 광역(廣域) 대기오염 정보는 국가적으로 공공 데이터를 통해 국민에게 제공하고 있으나, 환경변수가 다른 지역적인 대기오염 정보는 매우 부족한 상황이다. 따라서 본 연구에서는 지역적인 대기오염 현상을 보다 정확하게 분석하고 예측할 수 있는 지역 환경변수 기반의 대기오염 분석 및 예측 시스템을 설계하고 구현한다. 특히 제안한 시스템은 지역적으로 측정된 환경 데이터와 공공 빅데이터를 기반으로 지역의 대기정보를 정확하게 분석하여 제공하고, 인공지능 알고리즘을 통해 미래의 지역 대기정보를 예측하여 제시한다. 나아가 제안된 시스템을 통해 지역적인 대기오염의 발생 원인을 정확하게 파악하여 지역의 대기오염을 예방할 수 있을 것으로 기대할 수 있다.

• 한국환경보건학회지
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• 제44권6호
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• pp.563-571
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• 2018

Objectives: The purpose of this study was to investigate the environmental pollution caused by exposure to air pollution in Korea. Therefore, it is necessary to investigate environmental and health factors through big data. Methods: Among the environmental diseases, the data centered on "percentage per day in 2015 to 2018". Data of environmental diseases and concentrations of air pollution monitoring network were analyzed. Results: Lung cancer and bronchiolitis obliterans were correlated with 0.027 and 0.0158, respectively, in the contamination concentration of fine dust ($PM_{10}$). Ozone, COPD, allergic rhinitis, and bronchiolitis obliterans were correlated with 0.0022, 0.0028 and 0.0093, respectively. At the concentration of $SO_2$ and the diseases of asthma, atopic dermatitis, lung cancer and bronchiolitis obliterans were 0.0008, 0.0523, 0.0016 and 0.0126, respectively. Conclusions: We surveyed the trends of air pollution according to the characteristics of Seoul area in Korea and evaluated the perception of Korea and the world. As a result, respiratory lung disease is thought to be a major factor in exposure to environmental pollution.

• International Journal of Contents
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• 제18권1호
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• pp.17-26
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• 2022

With the acceleration of urbanization and industrialization, air pollution has become increasingly serious, and the pollution control situation is not optimistic. Climate change has become a major global challenge faced by mankind. To actively respond to climate change, China has proposed carbon peak and carbon neutral goals. However, atmospheric pollutants and meteorological factors that affect air quality are complex and changeable, and the complex relationship and correlation between them must be further clarified. This paper uses China's 2013-2018 high-resolution air pollution reanalysis open data set, as well as statistical methods of the Pearson Correlation Coefficient (PCC) to calculate and visualize the design and analysis of environmental monitoring big data, which is intuitive and it quickly demonstrated the correlation between pollutants and meteorological factors in the temporal and spatial sequence, and provided convenience for environmental management departments to use air quality routine monitoring data to enable dynamic decision-making, and promote global climate governance. The experimental results show that, apart from ozone, which is negatively correlated, the other pollutants are positively correlated; meteorological factors have a greater impact on pollutants, temperature and pollutants are negatively correlated, air pressure is positively correlated, and the correlation between humidity is insignificant. The wind speed has a significant negative correlation with the six pollutants, which has a greater impact on the diffusion of pollutants.

• 디지털콘텐츠학회 논문지
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• 제14권4호
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• pp.521-528
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• 2013

최근 날로 증가하는 자동차와 교통체증으로 인하여 대기 오염이 갈수록 심화되고 있으며, 인구가 밀집된 대도시에서의 대기 오염은 심각한 질병을 유발시키기도 한다. 본 연구에서는 이러한 대기 오염을 감소시키기 위하여, 대기 오염 정보를 효과적으로 전송하고 이를 이용하여 대기 오염이 한계치에 도달한 특정지역으로의 자동차 유입 억제 등에 활용할 수 있는 대기오염 정보 및 교통류 제어정보 전송 방안을 제안한다. 특히 대기오염 정보 및 교통류 제어 정보를 전송하는 방법으로 교통 및 여행정보 전송을 위한 국제표준기술인 TPEG이 적용되었다.

• Journal of Information Technology Applications and Management
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• 제28권6호
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• pp.87-95
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• 2021

Recently interest for air pollution is gradually increasing. However, according to the environmental assessment of air quality, the level of air pollution in the nation is quite serious, and air pollutants measuring facilities are also not enough. In this paper, a secure air pollutants sensor system based low power wireless communication is designed and implemented. The proposed system is composed of three parts: air pollutants measuring sensors module, LoRa-based data transmission module, and monitoring module. In the air pollutants measuring module, the MSP430 board with six big air pollutants measuring sensors are used. The air pollutants sensing data is transmitted to the control server in the monitoring system using LoRa transmission module. The received sensing data is stored in the database of the monitoring system, and visualized in real-time on the map of the sensor locations. The implemented air pollutant sensor system can be used for measuring the level of air quality conveniently in our daily lives.

• International Journal of Internet, Broadcasting and Communication
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• 제12권3호
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• pp.149-155
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• 2020

Air pollution is a problem of environmental health risk in big cities. Recently, researchers have proposed using various artificial intelligence technologies to predict air pollution. The proposed model is Cooperative of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS), to predict air pollution of Korean cities using Python. Data air pollutant variables were collected and the Air Korean Web site air quality index was downloaded. This paper's aim was to predict on the health risks and the very unhealthy values of air pollution. We have predicted the air pollution of the environment based on the air quality index. According to the results of the experiment, our model was able to predict a very unhealthy value.

• Tuberculosis and Respiratory Diseases
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• 제86권1호
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• pp.23-32
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• 2023

Everyone is aware that air and environmental pollutants are harmful to health. Among them, indoor air quality directly affects physical health, such as respiratory rather than outdoor air. However, studies that have examined the correlation between environmental and health information have been conducted with public data targeting large cohorts, and studies with real-time data analysis are insufficient. Therefore, this research explores the research with an indoor air quality monitoring (AQM) system based on developing environmental detection sensors and the internet of things to collect, monitor, and analyze environmental and health data from various data sources in real-time. It explores the usage of wearable devices for health monitoring systems. In addition, the availability of big data and artificial intelligence analysis and prediction has increased, investigating algorithmic studies for accurate prediction of hazardous environments and health impacts. Regarding health effects, techniques to prevent respiratory and related diseases were reviewed.

• 동아시아경상학회지
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• 제1권1호
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• pp.17-21
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• 2013

Purpose: Forecasting of petroleum consumption is useful in planning and management of petroleum production and control of air pollution. Research Design, Data and Methodology: ARMA models, sometimes called Box-Jenkins models after the iterative Box-Jenkins methodology usually used to estimate them, are typically applied to auto correlated time series data. Results: Petroleum consumption modeling plays a role key in big urban air pollution planning and management. In this study three models as, MLFF, MLFF with GARCH (1,1) and ARMA(1,1), have been investigated to model the petroleum consumption forecasts. Certain standard statistical parameters were used to evaluate the performance of the models developed in this study. Based upon the results obtained in this study and the consequent comparative analysis, it has been found that the MLFF with GARCH (1,1) have better forecasting results.. Conclusions: Survey of data reveals that deposit of government policies in recent yeas, petroleum consumption rises in Tehran and unfortunately more petroleum use causes to air pollution and bad environmental problems.

• 한국멀티미디어학회논문지
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• 제25권2호
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• pp.287-296
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• 2022

Today, air pollution is becoming a severe issue worldwide and various policies are being implemented to solve environmental pollution. In major cities, public bicycles are installed and operated to reduce pollution and solve transportation problems, and operational information is collected in real time. However, research using public bicycle operation information data has not been processed. This study uses the daily weather data of Korea Meteorological Agency and real-time air pollution data of Korea Environment Corporation to predict the amount of daily rental bicycles. Cross- validation, principal component analysis and multiple regression analysis were used to determine the independent variables of the predictive model. Then, the study selected the elements that satisfy the significance level, constructed a model, predicted the amount of daily rental bicycles, and measured the accuracy.

• Asian Journal of Business Environment
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• 제10권4호
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• pp.15-19
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• 2020

Purpose: This research aims to explore the level of air pollution in Jakarta, the epicenter of COVID-19 Pandemic in Indonesia and its surrounding provinces during the first month of the Pandemic. Research design, data and methodology: This study uses data, which have been obtained real time from API (Application Programming Interfaces) of air quality website. The measurements of Air Quality Index (AQI), temperature, humidity, and other factors from several cities and regencies in Indonesia were obtained eight times a day. The data collected have been analyzed using descriptive statistics and mapped using QGIS. Results: The finding of this study indicates that The Greater Jakarta Area experienced a decrease in pollutant levels, especially in the Bogor area. Nevertheless, some areas, such as the north Jakarta, have exhibited slow reduction. Furthermore, the regions with high COVID-19 confirmed cases have experienced a decline in AQI. Conclusions: The study concludes that the air quality of three provinces, Jakarta, Banten, and West Java, especially in cities located in the Jakarta Metropolitan Area during COVID-19 pandemic and large-scale social restrictions, is getting better. However, in some regions, the reduction of pollutant concentrations requires a longer time, as it was very high before the pandemic.