• Title/Summary/Keyword: Sensing and Application

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Abnormal current-voltage characteristics of $SnO_2$ oxide semiconductor and their application to gas sensors ($SnO_2$ 산화물 반도체의 비정상적 전류 - 전압 특성과 가스센서로의 응용)

  • Lee Kyu-chung;Yoon Ho-Kun;Hur Chang-Wu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.7
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    • pp.1436-1441
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    • 2004
  • Abnormal current-voltage characteristics of an oxide semiconductor have been investigated and a novel method of detecting reducing gases utilizing self-heating mechanism of sensing layer without an additional heater has been developed. Planar-type sensors based on WO3-doped SnO2 were fabricated using a screen-printing technique. The applied voltage across the sensing layer caused heating of the sensing layer and the current abruptly varied upon exposure to a gas mostly as a result of surface reactions. A unique and fascinating aspect of the gas sensing scheme is that no additional heater is necessary for detection. The new sensing method has been applied to C2H5OH gas in this preliminary work.

Development of Long-perimeter Intrusion Detection System Aided by deep Learning-based Distributed Fiber-optic Acoustic·vibration Sensing Technology (딥러닝 기반 광섬유 분포 음향·진동 계측기술을 활용한 장거리 외곽 침입감지 시스템 개발)

  • Kim, Huioon;Lee, Joo-young;Jung, Hyoyoung;Kim, Young Ho;Kwon, Jun Hyuk;Ki, Song Do;Kim, Myoung Jin
    • Journal of Sensor Science and Technology
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    • v.31 no.1
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    • pp.24-30
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    • 2022
  • Distributed fiber-optic acoustic·vibration sensing technology is becoming increasingly popular in many industrial and academic areas such as in securing large edifices, exploring underground seismic activity, monitoring oil well/reservoir, etc. Long-range perimeter intrusion detection exemplifies an application that not only detects intrusion, but also pinpoints where it happens and recognizes kinds of threats made along the perimeter where a single fiber cable was installed. In this study, we developed a distributed fiber-optic sensing device that measures a distributed acoustic·vibration signature (pattern) for intrusion detection. In addition, we demontrate the proposed deep learning algorithm and how it classifies various intrusion events. We evaluated the sensing device and deep learning algorithm in a practical testbed setup. The evaluation results confirm that the developed system is a promising intrusion detection system for long-distance and seamless recognition requirements.

Publishing a Web Based Crop Monitoring System and Performance Test (웹 기반 농업생산환경 모니터링 시스템 시범구축 및 성능평가)

  • Lee, Jung-Bin;Kim, Jeong-Hyun;Park, Yong-Nam;Hong, Suk-Young;Heo, Joon
    • Korean Journal of Remote Sensing
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    • v.31 no.5
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    • pp.491-499
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    • 2015
  • In developed countries such as USA and Europe, agricultural monitoring system is developed and utilized in various fields in order to predict crop yield, observe weather conditions and anomaly, categorize crop fields, and calculate areas for each crop. These system is Web Map Service(WMS) which utilizes open source and commercial softwares, and various information collected from remote sensing data are provided. This study will utilize tools such as GeoServer, ArcGIS Server, which are widely used to monitor agricultural production, to publish Map Server and Web Application Server. This enables performance test study for future agricultural production monitoring system by making use of response time and data transfer test. When tested in identical condition GeoServer showed a better result in response time and data transfer for performance test.

Relationship between sea ice concentration and sea ice albedo over Antarctica

  • Seo, Minji;Lee, Chang Suk;Kim, Hyunji;Huh, Morang;Han, Kyung-Soo
    • Korean Journal of Remote Sensing
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    • v.31 no.4
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    • pp.347-351
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    • 2015
  • Sea ice is a key parameter for understanding the climate change in cryosphere. In this study, we investigated the correlation with the factors that influenced change of the sea ice extent. We used the Sea Ice Concentration (SIC) from Ocean and Sea Ice Satellite Application Facility (OSI-SAF), and surface albedo provided by The Satellite Application Facility on Climate Monitoring (CM SAF). We converted the same temporal and spatial resolution of the data and detected the sea ice using SIC data. We performed the relationship analysis between SIC and sea ice albedo. As a result, we found they have a strong positive correlation. We performed the linear regression between SIC and sea ice albedo, and found they have high-level coefficient of determination. It shows using either SIC or sea ice albedo is possible to estimate the sea ice products.

Pan-sharpening Effect in Spatial Feature Extraction

  • Han, Dong-Yeob;Lee, Hyo-Seong
    • Korean Journal of Remote Sensing
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    • v.27 no.3
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    • pp.359-367
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    • 2011
  • A suitable pan-sharpening method has to be chosen with respect to the used spectral characteristic of the multispectral bands and the intended application. The research on pan-sharpening algorithm in improving the accuracy of image classification has been reported. For a classification, preserving the spectral information is important. Other applications such as road detection depend on a sharp and detailed display of the scene. Various criteria applied to scenes with different characteristics should be used to compare the pan-sharpening methods. The pan-sharpening methods in our research comprise rather common techniques like Brovey, IHS(Intensity Hue Saturation) transform, and PCA(Principal Component Analysis), and more complex approaches, including wavelet transformation. The extraction of matching pairs was performed through SIFT descriptor and Canny edge detector. The experiments showed that pan-sharpening techniques for spatial enhancement were effective for extracting point and linear features. As a result of the validation it clearly emphasized that a suitable pan-sharpening method has to be chosen with respect to the used spectral characteristic of the multispectral bands and the intended application. In future it is necessary to design hybrid pan-sharpening for the updating of features and land-use class of a map.

Preparation of Hydrogels Containing Polypyrrole@lignin Hybrids and Application in Sensors (전도성 고분자/리그닌 복합소재를 함유한 하이드로젤의 제조 및 센서 응용)

  • Park, Sun Young;Park, Soyeon;Kim, Hye Jun;Im, Youngsoon;Bae, Joonwon
    • Applied Chemistry for Engineering
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    • v.31 no.4
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    • pp.411-415
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    • 2020
  • In this article, the preparation of hydrogels containing conducting polymer@lignin hybrids and their application to sensing materials were demonstrated using diverse techniques. A conducting polymer, polypyrrole (PPy) was polymerized on the surface of lignin and successful formation was analyzed with Fourier-transform infrared spectroscopy and scanning electron microscopy. Subsequently, PPy@lignin hybrids were mixed with a hydrogel matrix to obtain a conductive hydrogel. The feasibility of using the hydrogel as a sensing material was shown by obtaining reasonable sensing signals using various electrical measurements when adding solvents and solutions to the sensor system. The significance of sensor signals was confirmed with complementary experiments. This study shows that the hydrogel containing the PPy@lignin could be used for sensor applications.

Application of Multi-periodic Harmonic Model for Classification of Multi-temporal Satellite Data: MODIS and GOCI Imagery

  • Jung, Myunghee;Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.35 no.4
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    • pp.573-587
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    • 2019
  • A multi-temporal approach using remotely sensed time series data obtained over multiple years is a very useful method for monitoring land covers and land-cover changes. While spectral-based methods at any particular time limits the application utility due to instability of the quality of data obtained at that time, the approach based on the temporal profile can produce more accurate results since data is analyzed from a long-term perspective rather than on one point in time. In this study, a multi-temporal approach applying a multi-periodic harmonic model is proposed for classification of remotely sensed data. A harmonic model characterizes the seasonal variation of a time series by four parameters: average level, frequency, phase, and amplitude. The availability of high-quality data is very important for multi-temporal analysis.An satellite image usually have many unobserved data and bad-quality data due to the influence of observation environment and sensing system, which impede the analysis and might possibly produce inaccurate results. Harmonic analysis is also very useful for real-time data reconstruction. Multi-periodic harmonic model is applied to the reconstructed data to classify land covers and monitor land-cover change by tracking the temporal profiles. The proposed method is tested with the MODIS and GOCI NDVI time series over the Korean Peninsula for 5 years from 2012 to 2016. The results show that the multi-periodic harmonic model has a great potential for classification of land-cover types and monitoring of land-cover changes through characterizing annual temporal dynamics.

Analysis of Tropospheric Carbon Monoxide in the Northeast Asia from MOPITT

  • Lee, Sang-Hee;Choi, Gi-Hyuk;Lim, Hyo-Suk;Lee, Joo-Hee
    • Korean Journal of Remote Sensing
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    • v.19 no.3
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    • pp.217-221
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    • 2003
  • The Measurement of Pollution in the Troposphere (MOPITT) instrument is an eight-channel gas correlation radiometer that launched on the Earth Observing System (EOS) Terra spacecraft in 1999. Its main objectives are to measure carbon monoxide (CO) and methane (CH4) concentrations in the troposphere. This study analyzes tropospheric carbon monoxide distributions using MOPITT data and compare with ozone distributions in Northeast Asia. In general, seasonal CO variations are characterized by a peak in spring and decrease in summer. Also, this study revealed that the seasonal cycles of CO are maximum in spring and minimum in summer with average concentrations ranging from 118ppbv to 170ppbv. The monthly average of CO shows a similar profile to those of O3. This fact clearly indicates that the high concentration of CO in spring is caused by two possible causes: the photochemical CO production in the troposphere, or the transport of the CO in the northeast Asia. The CO and $O_3$ seasonal cycles in the Northeast Asia are influenced extensively by the seasonal exchange of the different types of air mass due to the Asian monsoon. The continental air masses contain high concentrations of $O_3$ and CO due to higher continental background concentrations and sometimes due to the contribution of regional pollution. In summer the transport pattern is reversed. The Pacific marine air masses prevail over Korea, so that the marine air masses bring low concentrations of CO and $O_3$, which tend to give the apparent minimum in summer.

Assessment of a smartphone-based monitoring system and its application

  • Ahn, Hoyong;Choi, Chuluong;Yu, Yeon
    • Korean Journal of Remote Sensing
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    • v.30 no.3
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    • pp.383-397
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    • 2014
  • Information technology advances are allowing conventional surveillance systems to be combined with mobile communication technologies, creating ubiquitous monitoring systems. This paper proposes monitoring system that uses smart camera technology. We discuss the dependence of interior orientation parameters on calibration target sheets and compare the accuracy of a three-dimensional monitoring system with camera location calculated by space resectioning using a Digital Surface Model (DSM) generated from stereo images. A monitoring housing is designed to protect a camera from various weather conditions and to provide the camera for power generated from solar panel. A smart camera is installed in the monitoring housing. The smart camera is operated and controlled through an Android application. At last the accuracy of a three-dimensional monitoring system is evaluated using a DSM. The proposed system was then tested against a DSM created from ground control points determined by Global Positioning Systems (GPSs) and light detection and ranging data. The standard deviation of the differences between DSMs are less than 0.12 m. Therefore the monitoring system is appropriate for extracting the information of objects' position and deformation as well as monitoring them. Through incorporation of components, such as camera housing, a solar power supply, the smart camera the system can be used as a ubiquitous monitoring system.

Cloud-based Satellite Image Processing Service by Open Source Stack: A KARI Case

  • Lee, Kiwon;Kang, Sanggoo;Kim, Kwangseob;Chae, Tae-Byeong
    • Korean Journal of Remote Sensing
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    • v.33 no.4
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    • pp.339-350
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    • 2017
  • In recent, cloud computing paradigm and open source as a huge trend in the Information Communication Technology (ICT) are widely applied, being closely interrelated to each other in the various applications. The integrated services by both technologies is generally regarded as one of a prospective web-based business models impacting the concerned industries. In spite of progressing those technologies, there are a few application cases in the geo-based application domains. The purpose of this study is to develop a cloud-based service system for satellite image processing based on the pure and full open source. On the OpenStack, cloud computing open source, virtual servers for system management by open source stack and image processing functionalities provided by OTB have been built or constructed. In this stage, practical image processing functions for KOMPSAT within this service system are thresholding segmentation, pan-sharpening with multi-resolution image sets, change detection with paired image sets. This is the first case in which a government-supporting space science institution provides cloud-based services for satellite image processing functionalities based on pure open source stack. It is expected that this implemented system can expand with further image processing algorithms using public and open data sets.