• 제목/요약/키워드: air pollution detection

검색결과 60건 처리시간 0.025초

Satellite monitoring of large-scale air pollution in East Asia

  • Chung, Y.S.;Park, K.H.;Kim, H.S.;Kim, Y.S.
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.786-789
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    • 2003
  • The detection of sandstorms and industrial pollutants has been the emphasis of this study. Data obtained from meteorological satellites, NOAA and GMS, have been used for detailed analysis. MODIS and Landsat images are also used for the application of future KOMPSAT- 2. Verification of satellite observations has been made with air pollution data obtained by ground-level monitors. It was found that satellite measurements agree well with concentrations and variations of air pollutants measured on the ground, and that satellite technique is a very useful device for monitoring large-scale air pollution in East Asia. The quantitative analysis of satellite image data on air pollution is the goal in the future studies.

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A Study on Environmental Micro-Dust Level Detection and Remote Monitoring of Outdoor Facilities

  • Kim, Seung Kyun;Mariappan, Vinayagam;Cha, Jae Sang
    • International journal of advanced smart convergence
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    • 제9권1호
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    • pp.63-69
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    • 2020
  • The rapid development in modern industrialization pollutant the water and atmospheric air across the globe that have a major impact on the human and livings health. In worldwide, every country government increasing the importance to improve the outdoor air pollution monitoring and control to provide quality of life and prevent the citizens and livings life from hazard disease. We proposed the environmental dust level detection method for outdoor facilities using sensor fusion technology to measure precise micro-dust level and monitor in realtime. In this proposed approach use the camera sensor and commercial dust level sensor data to predict the micro-dust level with data fusion method. The camera sensor based dust level detection uses the optical flow based machine learning method to detect the dust level and then fused with commercial dust level sensor data to predict the precise micro-dust level of the outdoor facilities and send the dust level informations to the outdoor air pollution monitoring system. The proposed method implemented on raspberry pi based open-source hardware with Internet-of-Things (IoT) framework and evaluated the performance of the system in realtime. The experimental results confirm that the proposed micro-dust level detection is precise and reliable in sensing the air dust and pollution, which helps to indicate the change in the air pollution more precisely than the commercial sensor based method in some extent.

지하철 역내 가스 검출 원격 모니터링 시스템 구현 (Development of a remote monitoring system for gas detection at the subway station)

  • 박용만;김희식;김규식;이문규
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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    • pp.439-441
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    • 2007
  • The seoul metropolitan subway has installed 8 lines and about 500 stations to transport 5 million passengers everyday. The underground air pollution level in the subway stations is very severe status, which is very harmful to the commutators and its personals. Although subway roles as such a massive and huge transportation system, the subway doesn't adapt yet any real-time air monitoring system. They have only some hand-held type detector equipments for monitoring air pollution. Therefore subway passengers are exposed to the harmful air pollution environment. The most harmful environmental parameters among the air pollution are known as the dust and sound noise dB level in the subway station. Because the dust is consisted of very small particles, we can't see them easily in dark condition on the platform, but it is very harmful. The monitoring system for air pollution is developed using embedded system attached with 6 different environmental sensors. This system monitors air pollution of dust sound noise, gas, temperature, humidity, inflammable gas, toxic gas in the subway ?station. The sensor unit of the ARM-CPU board and sensor transmits real time environmental data to the main server using Zigbee wireless communication module and TCP/IP network. The main control server receives and displays the real-time environmental data, and it send alarms to the personals when high level value.

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Review of Internet of Things-Based Artificial Intelligence Analysis Method through Real-Time Indoor Air Quality and Health Effect Monitoring: Focusing on Indoor Air Pollution That Are Harmful to the Respiratory Organ

  • Eunmi Mun;Jaehyuk Cho
    • 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.

정확한 대기오염물질 배출 지정 탐지를 위한 드론 비행 궤도에 관한 연구 (A Study on Drone Flight Trajectory for Accurate Detection of Air Pollutant Emission Designation)

  • 김수영;이석훈;정동원
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 추계학술대회
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    • pp.15-17
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    • 2021
  • 이 논문에서는 정확한 대기오염물질 배출 지정 탐지를 위한 드론 비행 궤도 방법을 제안한다. 공단과 같이 공장이 많은 지역에서 감시가 소홀한 상황에 대기오염물질을 불법 배출하는 사업장들이 존재한다. 기존에는 드론을 이용하여 이러한 지역에서 대기오염물질을 측정하기 위한 연구들이 활발히 진행되었다. 드론을 활용한 측정 방법은 공장의 굴뚝 주변에 멈춰서 오염을 탐지하는 방식을 사용하지만, 기압과 바람 등의 환경 요소에 따라 대기오염물질 탐지가 부정확하다는 문제를 지닌다. 따라서 이 논문에서는 정확한 대기오염물질 배출 지정 탐지를 위한 드론 비행 궤도 방법을 제안한다. 제안 방법은 드론이 굴뚝을 회전하면서 위로 비행하는 스크류 궤도 비행 방법으로, 굴뚝의 전체 면적을 탐지하고 환경요소를 고려해 측정한다. 실험에서 제안 방법이 기존 방법보다 나은 성능을 보였다.

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Detection of Phototoxicity and Photogenotoxicity on Airborne Particulates in Sapporo and Shenyang

  • Wakuri, Shinobu;Akutagawa, Tomoko;Matsumoto, Hiroshi;Tanaka, Noriho
    • 한국독성학회:학술대회논문집
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    • 한국독성학회 2003년도 추계학술대회
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    • pp.112-112
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    • 2003
  • Air pollution is made up by complex mixture exhausted from cars, industries and incinerators etc. Those pollutants come from everywhere without border and contain phototoxic and photogenotoxic chemicals including PAHs exhausted in the air. We have published that the chemicals which show phototoxicity and photogenotoxicity are closely related in mechanistic and the PAHs react as a strong photocatalyzer by radical productions under UV exposure.(omitted)

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NDIR 검출기를 이용하는 대기오염 측정시스템을 위한 미세신호 검출 알고리즘 (Minute Signal Detection Algorithm for Air-pollution Measurement System with The NDIR Detector)

  • 최훈;김현호;황병한;임용석;류근택;배현덕
    • 전자공학회논문지 IE
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    • 제45권3호
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    • pp.27-35
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    • 2008
  • 본 논문은 다중 가스 필터 휠 (multi gas filter correlation wheel: multi GFC wheel)을 갖는 비분산 적외선법(NDIR method : non-dispersive infrared method)을 이용하여 대기 중 다종환경오염물질(CO, $SO_2$, NOx 등)을 동시에 실시간 측정할 수 있는 광학분석장치 개발을 위한 미세신호 검출 알고리즘을 제안한다. MCT(mercury cadmium telluride) 센서를 통해 측정된 각각의 환경오염물질의 미세신호는 고유한 NDIR 흡수 특성을 갖는다. 제안한 방법은 임계값과 하나의 외부 동기신호를 사용하여 연속적으로 측정된 신호로부터 각각의 오염물질 특정농도에 해당하는 데이터를 분리 검출한다.

고해상도 원격탐사 영상을 이용한 YOLOv5기반 굴뚝 탐지 (YOLOv5-based Chimney Detection Using High Resolution Remote Sensing Images)

  • 윤영웅;정형섭;이원진
    • 대한원격탐사학회지
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    • 제38권6_2호
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    • pp.1677-1689
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    • 2022
  • 대기오염은 동식물의 건강에 장·단기적으로 해로운 영향을 미치는 사회적 문제이다. 굴뚝은 대기를 오염시키는 대기오염물질의 주배출원으로 그 위치와 종류를 탐지하고 모니터링할 필요가 있다. 대기오염물질을 배출하는 굴뚝이 위치한 발전소 및 산업단지는 접근성이 많이 떨어지고 부지가 넓어 직접 모니터링하기에는 비용적, 시간적으로 비효율적이다. 따라서 최근에는 원격탐사 자료를 이용하여 굴뚝을 탐지하는 연구가 수행되고 있다. 본 연구에서는 중국 베이징, 톈진 허베이 성에 위치한 발전소를 대상으로 구축된 BUAA-FFPP60 오픈 데이터 세트를 활용하여 YOLOv5기반의 굴뚝 탐지 모델을 제작하였다. 탐지 모델의 성능을 향상시키기 위하여 데이터 분할과 데이터 증강기법을 적용하였으며, 최적의 모델 제작을 위한 학습 전략을 세웠다. 학습이 완료된 모델은 precision, recall과 같은 각종 지표를 통해 성능을 확인하였으며, 최종적으로 동일한 데이터 세트를 사용한 기존 연구와의 비교를 통해 모델의 성능을 평가하였다.