• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.429-430
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• 2022

본 논문에서는 일산화탄소 센서와 미세먼지 센서를 이용하여 연기농도에 따른 감도시험을 수행하였다. 일산화탄소 센서와 미세먼지 센서는 광전식감지기 감도시험 챔버 내에서 발생시킨 연기농도에 따라 감지반응이 있었으며, 다양한 화재정보를 제공을 위해 가스 센서 및 미세먼지 센서가 기술기준 도입이 필요할 것으로 사료된다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.67-68
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• 2020

본 논문에서는 미세먼지 센서와 가스 센서를 이용한 효율적인 스마트 홈 기반 다중 센서 알림 시스템을 제안한다. 시스템은 여러 유형의 홈 센서를 이용하여 효율적으로 미세먼지와 실내의 가스를 탐지 후 실시간으로 애플리케이션을 통해서 사용자에게 탐지 결과를 알려주는 시스템이다. 본 시스템의 경우 기존에 존재하는 미세먼지 센서와 가스 센서를 적용한 측정 시스템에 비해 소액으로 최적의 시스템을 구축할 수 있다. 시스템은 기존의 가스 센서와 다르게 한 번에 다양한 종류의 가스를 탐지해 사용자에게 여러 정보를 제공할 수 있도록 개발하였다.

• 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.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.234-235
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• 2018

본 논문에서는 R.Box와 연결되어 미세먼지정보를 무선으로 전송하는 아두이노 기반의 시스템을 제안한다. R.Box는 라즈베리파이를 기반으로 다양한 센서로 구성된 일반목적의 IoT 허브이다. 아두이노와 미세먼지센서를 이용해 미세먼지농도를 측정하고 데이터를 WiFi를 통해 R.Box로 전송한다. 아두이노와 R.Box는 TCP 소켓 방식으로 통신하며 이 시스템을 통하여 원하는 위치의 미세먼지정보를 확인할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.90-91
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• 2023

대기오염에 대한 사회적 관심이 증가함에 따라 미세먼지 관련 IoT 가전제품의 수요가 증가하였다. 이에 따라 IoT 제품에서 수집되는 실내 데이터의 정확성을 높이기 위해 미세먼지 센서 외의 추가적인 센서를 사용하여 관측치를 예측하는 연구가 진행되고 있다. 하지만 기존 연구에서는 센서의 물리적 한계를 인공지능을 통하여 극복하려는 시도는 존재하지 않는다. 본 논문에서는 추가적인 센서를 사용하지 않고 단일 센서만을 사용하여 미세먼지 종류의 구분 가능성을 판단하고자 하며 이를 정확도 기반으로 비교 실험을 진행하여 가장 좋은 성능을 나타낸 딥러닝 기반 분류모델을 선정한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.703-704
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• 2021

도로변에서 발생하는 미세먼지와 비산먼지는 인체에 각종 질병을 유발하는 발암물질로 알려져 있다. 본 논문에서는 효율적인 도로변 미세먼지의 농도를 측정을 위해 소형차량을 이용한 이동형 미세먼지 모니터링 시스템을 제안한다. 이 시스템은 기존의 대형차량의 운행으로 발행하는 미세먼지 사각지대를 해소하고, 고품질의 보급형 센서를 탑재하여 경제성을 제고한다. 또한, 미세먼지 측정 차량은 이동 중에도 실시간으로 측정가능하다. 이번 연구를 통해 미세먼지 측정 차량을 운행한 결과 도로변 상황을 즉각적으로 반영하는 결과를 나타내었다. 이러한 미세먼지 농도는 미세먼지 저감 및 관리를 위한 기초정보로 사용될 것을 기대한다.

• The Journal of the Acoustical Society of Korea
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• v.42 no.1
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• pp.7-15
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• 2023

Recently, as interest in air quality in vehicles increases, the use of fine dust detection sensors for air quality measurement is becoming common. An axial-flow fan is inserted in the fine dust sensor installed in the air conditioning system in the vehicle to prevent dust from sinking directly on the sensor. When the sensor operates, the flow noise caused by the rotation of the axial-flow fan acts as a major noise source of the fine dust sensor. flow noise is recognized as one of the product competitiveness of fine dust sensors. In this study, the noise was gradually reduced at the same flow rate by improving the flow performance of the small axial flow fan. First, a virtual fan performance tester consisting of about 20 million grids was developed to analyze the aerodynamic performance of the target small axial-flow fan. In addition, the flow field was simulated by using compressible Large Eddy Simulation for direct computation of flow noise as well as high-accurate prediction of flow rate. The validity of numerical method are confirmed through the comparison of predicted results with experimental ones. After the effects of pitch angle on flow performance were analyzed using the verified numerical method, the pitch angle was determined to maximize the flow rate. It was found that the flow rate was increased by 8.1 % and noise was reduced by 0.8 dBA when the axial-flow fan with the optimum pitch angle was used.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.119-125
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• 2019

Recently, it has become a social problem due to fine particles. There are more people wearing masks, weather alerts and disaster notices. Research and policy are actively underway. Meteorologically, the biggest damage caused by fine particles is the inversion layer phenomenon. In this study, we designed a system to warn fine Particles by analyzing inversion layer and wind direction. This weather information system proposes a system that can efficiently perform scalability and parallel processing by using OGC sensor web enablement system and NoSQL storage for sensor control and data exchange.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.125-132
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• 2020

Due to the rapidly increasing number of cars and power generation, environmental pollution caused by fine dust is becoming a serious social problem. Especially fine dust becomes an important issue nowadays. More than 50 countries are suffering from fine dust above the recommended level, and each affected country is studying the measures to reduce fine dust and minimize its occurrence. However, at present, it is difficult to collect fine dust data from the various points with fixed fine dust acquisition drones, and also to collect accurate data due to the influence of rotating blades even in the existing drone method. In this paper, we propose a method for collecting fine dust using drones and a sensing parts architecture and show its effectiveness.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.344-346
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• 2018

Air pollution has become a social issue. Particularly, interest in fine dust is increasing. Various kinds of sensors are being used to measure fine dust. The most commonly used infrared detection dust sensors operate by sensing the diffraction of light through an infrared receiver and sensing the light reflected by the dust in the air. However, this method has a drawback in which accurate data analysis is difficult due to deviation caused by the noise during measurement. In order to overcome such drawbacks, in this thesis, a low pass filter algorithm of FIR(Finite Impulse Response) filter was designed and implemented.