• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1681-1690
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• 2020

A scanning lidar system has been developed. The system has two wavelength observation channels of 532 and 1064 nm and is capable of 360-degree horizontal scanning observation. In addition, an analysis method that can classify the measured particle as an indicator of coarse-mode particle (PM2.5-10) and an indicator of fine-mode particles (PM2.5) and calculate the mass concentration of each has been developed by using the backscatter coefficient at two wavelengths. It was applied to the data calculated by observation. The mass concentrations of PM10 and PM2.5, which showed a distribution of 22-110 ㎍/㎥ and 7-78 ㎍/㎥, respectively, were successfully calculated in the Ulsan Onsan Industrial Complex using the developed scanning lidar system. The analyzed results showed similar values to the mass concentrations measured on the ground around the lidar observation area, and it was confirmed that high concentrations of 80-110 ㎍/㎥ and 60-78 ㎍/㎥ were measured at points discharged from factories, respectively.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.75-82
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• 2018

Efforts to reduce damages from micro dust and harmful gases in life have been led by national or local governments, and information on air quality has been provided along with real-time weather forecast through TV and internet. It is not enough to provide information on the individual indoor space consumed. So in this paper, we propose a IoT-based Real-Time Air Quality Sensing Board Corresponding Fine Particle for Air Quality Management in Buildings. Proposed board is easy to install and can be placed in the right place. In the proposed board, the air quality (level of pollution level) in the indoor space (inside the building) is easy and it is possible to recognize the changed indoor air pollution situation and provide countermeasures. According to the advantages of proposed system, it is possible to provide useful information by linking information about the overall indoor space where at least one representative point is located. In this paper, we compare the performance of the proposed board with the existing air quality measurement equipment.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.443-444
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• 2022

본 논문에서는 스타일러는 옷을 빨거나 다리지 않고도 마치 새옷처럼 다시 입을 수 있도록 관리해준다는 콘셉트로 등장한 의류기기이다. 출시 당시에는 생소하고 크기가 커서 큰 호응을 얻지 못했지만, 최근에는 작고 편리한 신제품을 내놓으면서 대중화 시대를 열어가고 있다. 양복을 주로 입는 회사원에서 싱글족까지 스타일러를 사용하고 있지만 대중적인 스타일러는 정해진 위치에서만 사용해야 한다는 불편함이 있다. 또한 출장이 잦은 직업이나 먼지가 많은 공간에서 일하는 직업의 경우 옷에 주름이나 먼지를 제거하지 못해 구겨진 옷을 입고 다니는 경우가 많다. 그래서 우리는 가정용 스타일러에서 장소에 구애받지 않고 사용할 수 있는 휴대용 스마트 스타일러를 제작하기로 하였다. 예기치 못한 상황에서의 중요한 자리가 있을 때 휴대용 스타일러가 있다면 준비해둔 의류를 상황에 맞춰 관리하여 다닐 수 있을 것이며, 스타일러에 온도와 습도를 보여주는 기능이 있다면 스타일러를 사용하기 전에 스타일러의 상태가 양호한지 판단할 수 있을 것이다.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.109-127
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• 2011

Atmospheric aerosols, small particles in the atmosphere, are one of the important parameters in climate change and human health. Additionally, accurate estimates of aerosol species are increasingly important in environmental impact assessment studies. Recent advances in global satellite remote sensing provide powerful tool for air quality monitoring. This study explores the potential usage of satellite derived data such as atmospheric aerosols for air quality monitoring as well as climate change study. The objectives of this study is to understand the general features of the global distribution of type dependent aerosols. A detailed spatio-temporal variability of the each different satellite dataset shows the variation of the global zonal average and specific geographical regions where the strong emission sources are located. Especially, significantly large aerosol amounts are observed in Asia and Africa because of the desert dust storm, anthropogenic and biomass burning emissions.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.56-61
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• 2017

Recently, the satellite development project in Korea has been changing from demand to focus on various purposes. Especially, it is proposed to process satellite data from a simple terrestrial image observation satellite and to produce high value added information. In order to expand demand for satellite information, it is necessary to develop customized information and to provide information that reflects the needs of the final target population. In this study, we conducted a questionnaire survey and analyzed the results to analyze the requirements for the customized services of environmental satellites. As a result, the environmental satellites were found to have a low awareness due to the launch and operation, but they were highly aware of the recent environmental issues such as fine dust. In addition, they are aware of the necessity of developing independent environmental satellites because they have a strong desire for environmental security, and they prefer to provide materials through media that are easy to publicize and access through the media.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.21-27
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• 2022

As society develops and becomes more complex, new and diverse types of disasters such as fine dust and infectious diseases are occurring. However, in the past, there was no PA(Public Address) system that provided accurate information to prepare for such a disaster. In this paper, we propose a public address system that automatically broadcasts an alarm by analyzing polluted air quality data collected from public data and IoT sensors. The warning level varies depending on the air quality, and the information provided by public data may show a significantly different result from the guide area due to various factors such as the distance from the measuring station or the wind direction. To compensate for this, we are going to propose a method for broadcasting by comparing and analyzing data obtained from public data and data from on-site IoT sensors.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.495-505
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• 2006

In order to classify aerosol type, Aerosol Optical Thickness (AOT) and Fine mode Fraction (FF), which is the optical thickness ratio of small particles$(<1{\mu}m)$ to total particles, data from MODIS (MODerate Imaging Spectraradiometer) aerosol products were analyzed over North-East Asia during one year period of 2005. A study area was in the ocean region of $20^{\circ}N\sim50^{\circ}N$ and $110^{\circ}E\simt50^{\circ}E$. Three main atmospheric aerosols such as dust, sea-salt, and pollution can be classified by using the relationship between AOT and FF. Dust aerosol has frequently observed over the study area with relatively high aerosol loading (AOT>0.3) of large particles (FF<0.65) and its contribution to total AOT in spring was up to 24.0%. Pollution aerosol, which is originated from anthropogenic sources as well as a natural process like biomass burning, has observed in the regime of high FF (>0.65) with wide AOT variation. Average pollution AOT was $0.31{\pm}0.05$ and its contribution to total AOT was 79.8% in summer. Characteristic of sea-salt aerosol was identified with low AOT (<0.3), almost below 0.1, and slightly higher FF than dust and lower FF than pollution. Seasonal analysis results show that maximum AOT $(0.33{\pm}0.11)$ with FF $(0.66{\pm}0.21)$ in spring and minimum AOT $(0.19{\pm}0.05)$, FF $(0.60{\pm}0.14)$ in fall were observed in the study area. Spatial characteristic was that AOT increasing trend is observed as closing to the eastern part of China due to transport of aerosols from China by the prevailing westerlies.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1191-1205
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• 2022

Particulate matter(PM) among air pollutants with complex and widespread causes is classified according to particle size. Among them, PM_2.5 is very small in size and can cause diseases in the human respiratory tract or cardiovascular system if inhaled by humans. In order to prepare for these risks, state-centered management and preventable monitoring and forecasting are important. This study tried to predict PM_2.5 in Seoul, where high concentrations of fine dust occur frequently, using two ensemble models, random forest (RF) and extreme gradient boosting (XGB) using 15 local data assimilation and prediction system (LDAPS) weather-related factors, aerosol optical depth (AOD) and 4 chemical factors as independent variables. Performance evaluation and factor importance evaluation of the two models used for prediction were performed, and seasonal model analysis was also performed. As a result of prediction accuracy, RF showed high prediction accuracy of R² = 0.85 and XGB R² = 0.91, and it was confirmed that XGB was a more suitable model for PM_2.5 prediction than RF. As a result of the seasonal model analysis, it can be said that the prediction performance was good compared to the observed values with high concentrations in spring. In this study, PM_2.5 of Seoul was predicted using various factors, and an ensemble-based PM_2.5 prediction model showing good performance was constructed.