• 한국토양비료학회지
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• 제50권3호
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• pp.162-178
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• 2017

Remote sensing can be used to provide information about the monitoring of crop growth condition. Recently Unmanned Aerial Vehicle (UAV) technology offers new opportunities for assessing crop growth condition using UAV imagery. The objective of this study was to assess weather UAV aerial images are suitable for the monitoring of highland Kimchi cabbage. This study was conducted using a fixed-wing UAV (Model : Ebee) with Cannon S110, IXUS/ELPH camera during farming season from 2015 to 2016 in the main production area of highland Kimchi cabbage, Anbandegi, Maebongsan, and Gwinemi. The Normalized Difference Vegetation Index (NDVI) by using UAV images was stable and suitable for monitoring of Kimchi cabbage situation. There were strong relationships between UAV NDVI and the growth parameters (the plant height and leaf width) ($R^2{\geq}0.94$). The tendency of UAV NDVI according to Kimchi cabbage growth was similar in the same area for two years (2015~2016). It means that if UAV image may be collected several years, UAV images could be used for estimation of the stage of growth and situation of Kimchi cabbage cultivation.

• Journal of Advanced Marine Engineering and Technology
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• 제32권6호
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• pp.989-996
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• 2008

Recently, a few types of fish-cage in open sea are researched. This fish-cage has to operate monitoring system for keeping an optimum living condition for fish. The most efficient monitoring system is WVMS(Wireless Vision Monitoring System) for fish-cage in open sea. WVMS should be able to transmit video signal and communicate with each controller. So. it needs to be based on WLAN(Wireless LAN) which has characteristic of higher transfer-rate, In this paper, we propose a structure of WVMS using WLAN equipments for maritime environment and prove its effectiveness. We present the propagation loss model of WVMS's communication channel. measured by field test, and discuss its validity compared with the predictive value based on the Friss propagation model and Plane earth reflection model. We present the number of frames that is received from WLAN modem connecting with underwater-camera in field test spots. As a result, we confirmed that proposed WVMS is suitable for maritime environment and it is possible to be applied to fish-cage in open sea on 'seogwipo'.

• 한국정밀공학회지
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• 제30권7호
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• pp.687-693
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• 2013

The service conditions of railway cars have become more difficult in recent years due to increased speed. Faulty components in the railcars may result in service interruption, or in extreme cases, derailment. Thus, it is important to diagnose and monitor the main components of railcars. Temperature monitoring is one of the basic methods used to diagnose abnormal conditions in the main components of railway cars, such as in bearings, reduction gears, and traction motors. In this study, we developed a monitoring system for the main components, using an infrared thermography technique. This technique has the advantage of infrared thermal camera imaging of temperature contours in the components. Various hardware and software components of the monitoring system are used to acquire the sensor data, to identify potential problems in railcar operation.

• Journal of Advanced Marine Engineering and Technology
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• 제38권10호
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• pp.1275-1280
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• 2014

In this study, the performance of a real-time micro telescopic monitoring system is evaluated, in which an artificial neural network is adopted for the diagnoses of vibratory bodies, such as solid piping system or machinery. The structural vibration was measured by a non-contact remote sensing method, in which images of a high-speed high-definition camera were used. The structural vibration data that can be obtained by the PIV (particle image velocimetry) technique were used for training the neural network. The structures of the neural network are dynamically changed and their performances are evaluated for the constructed diagnosis system. Optimized structures of the neural network are proposed for real-time diagnosis for the piping system. It was experimentally verified that the performances of the neural network used for real-time monitoring are influenced by the types of the vibration data, such as minimum, maximum and average values of the vibration data. It concludes that the time-mean values are most appropriate for monitoring the piping system.

• 융합신호처리학회논문지
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• 제11권1호
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• pp.9-12
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• 2010

본 논문은 재난 감시를 위한 디지털 미디어 프로세서 기반의 적외선 열화상 처리 시스템의 설계 및 구현에 대하여 기술한다. 디지털 열화상 처리 보드는 DM642 디지털 미디어 프로세서와 비디오 인코더, 비디오 디코더 상용 칩을 기반으로 설계하고 구현하였다. 또한, 재난 감시 기능은 적외선 열화상의 온도분포를 분석하고 화재발생과 같은 재난상황을 감시하는 알고리즘을 구현하였으며, 적외선 열화상 입력은 $320\;{\times}\;240\;{\mu}$-bolometer 타입의 적외선 열화상 카메라를 사용하였다. 구현된 시제품의 시험 평가 결과, 10 프레임/초의 처리 속도로 요구되는 적외선 열화상 분석과 화재 검출 기능이 잘 동작 하였으며 구현 시스템의 실용성을 확인하였다.

• 제어로봇시스템학회논문지
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• 제3권3호
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• pp.318-322
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• 1997

A prototype of combustion zone monitoring system as been developed and installed into tuyeres of the blast furnace. The system consists of CCD(charge coupled device) cameras, sonic flow meters, an image processor and a personal computer. The personal computer collects raceway luminance data and operational data from the image processor that is connected to the color CCD camera from the blast furnace process computer, respectively. In addition, the sonic flow meters supply coal injection rate data to the personal computer. Then, the personal computer evaluates the combustion conditions with the raceway inspection algorithm. This integrated monitoring system allows us to detect abnormal raceway conditions and the clogging status of coal injection pipe. The image processing techniques of the system enable us to effectively monitor unburnt coal sticking to tuyere tip and injection lance wear conditions. Such a developed system ensures rapid and precise raceway inspection. The image processing capability of the system has helped operator to early detect both the unburnt coal sticking problem and the errosion problem of injection lance. Furthermore, the system could control the abnormal raceway condition based the the analysis results obtained from combustion monitoring.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• Nuclear Engineering and Technology
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• 제54권12호
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• pp.4679-4683
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• 2022

Environmental radiation monitoring is required to protect from the effects of radiation in industrial fields such as nuclear power plant (NPP) monitoring, and various gamma camera systems are being developed. The purpose of this study is to optimize parameters of a diverging collimator composed of pure tungsten for compactness and lightness through Monte Carlo simulation. We conducted the performance evaluation based on spatial resolution and signal-to-noise ratio for point source and obtained gamma images and profiles. As a result, optimization was determined at a collimator height of 60.0 mm, a hole size of 1.5 mm, and a septal thickness of 1.0 mm. Also, the full-width-at-half-maximum was 3.5 mm and the signal-to-noise ratio was 53.5. This study proposes a compact 45° diverging collimator structure that can quickly and accurately identify the location of the source for radiation monitoring.

• 터널과지하공간
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• 제20권3호
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• pp.207-216
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• 2010

국내에서 현재까지 개발되어 적용된 낙석감지 시스템은 주로 낙석방지망에 와이어나 광섬유, 또는 경사계를 설치하여 와이어의 장력을 측정하거나 낙석 발생에 의해 와이어 단락이나 낙석방지망의 변형 또는 기울어지는 것을 감지하여 낙석을 확인하는 시스템들이다. 이러한 방법들은 낙석방지망이 먼저 설치되어 있어야 하며 낙석이 발생하면 일반적으로 관련 센서와 와이어 등에 대하여 재정비를 해야 다시 원래의 기능을 수행할 수 있게 된다. 이러한 단점을 해결하기 위하여 본 연구에서는 장력이나 변위 측정방식이 아니라 광센서와 카메라가 설치된 구역에서 낙석 통과 여부를 비접촉 방식으로 실시간 감지가 가능하도록 하는 방법을 제시하고 이를 구현하였다. 개발된 시스템을 실내실험 및 현장 적용을 한 결과 낙석 관련 정보를 효과적으로 수집하고 분석할 수 있었다. 또한 낙석 감지 전후 획득한 2장의 사진에 대하여 lighten 또는 difference 연산을 적용할 경우 낙석의 크기와 이동 방향에 대한 개략적 평가가 가능하였다.

• 한국위성정보통신학회논문지
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• 제11권3호
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• pp.18-23
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• 2016

의료 센터에서 데이터 분석과 스마트폰 어플리케이션 권한을 부여함으로써 사물 인터넷 (IoT)은 환자 중심의 의료 관찰과 관리에서 대혁변을 일으킬 것이다. 네트워크 연결은 개인 의료 서비스에서 IoT 의학 장치로 부터 건강을 관찰하는 스마트폰으로부터 진료받는 사람들의 건강 정보를 모으기 위한 기본 요구사항이다. 스마트폰에 설치된 IoT 환경은 매우 효과적이고 이것은 사회 기반 시설을 필요로 하지 않는다. 본 논문은 ECG 캡처링에 영향을 주지 않기 위해 스마트폰이 개인 IoT 아키텍처를 효율적으로 사용하는 것을 보여준다. 적응 IoT 의료 장치 관문은 클라우드 구성에 관한 대용량을 가진 개인 의료 서비스에 사용된다. 이 접근법에서, 스마트폰 카메라는 개인 ECG 파형을 추출하기 위해 사용된 이미지 기술을 기반으로 하고, 그것을 IoT 아키텍처를 사용한 대용량 저장 연결에 근거한 클라우드로 보낸다. 정교해진 알고리즘은 스마트폰이나 테블릿 카메라로 부터 찍힌 얼굴이미지로 부터 효율적인 ECG 등록을 직접 가능할 수 있는 여지를 준다. 이 심도있는 기술은 아마 적절한 기능 강화들이 소개된 후에 개인 의료 서비스를 관찰하는데 있어서 특별한 가치를 가질 것이다.