• The Journal of Korea Robotics Society
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• v.12 no.4
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• pp.432-440
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• 2017

In this paper, we propose a jellyfish distribution recognition and monitoring system using a UAV (unmanned aerial vehicle). The UAV was designed to satisfy the requirements for flight in ocean environment. The target jellyfish, Aurelia aurita, is recognized through convolutional neural network and its distribution is calculated. The modified deep neural network architecture has been developed to have reliable recognition accuracy and fast operation speed. Recognition speed is about 400 times faster than GoogLeNet by using a lightweight network architecture. We also introduce the method for selecting candidates to be used as inputs to the proposed network. The recognition accuracy of the jellyfish is improved by removing the probability value of the meaningless class among the probability vectors of the evaluated input image and re-evaluating it by normalization. The jellyfish distribution is calculated based on the unit jellyfish image recognized. The distribution level is defined by using the novelty concept of the distribution map buffer.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.6
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• pp.731-742
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• 2016

Recent technological advance in UAV (Unmanned Aerial Vehicle) technology offers new opportunities for assessing crop situation using UAV imagery. The objective of this study was to assess if reflectance and NDVI derived from consumer-grade cameras mounted on UAVs are useful for crop condition monitoring. This study was conducted using a fixed-wing UAV(Ebee) with Cannon S110 camera from March 2015 to March 2016 in the experiment field of National Institute of Agricultural Sciences. Results were compared with ground-based recordings obtained from consumer-grade cameras and ground multi-spectral sensors. The relationship between raw digital numbers (DNs) of UAV images and measured calibration tarp reflectance was quadratic. Surface (lawn grass, stairs, and soybean cultivation area) reflectance obtained from UAV images was not similar to reflectance measured by ground-based sensors. But NDVI based on UAV imagery was similar to NDVI calculated by ground-based sensors.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.275-275
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• 2019

기후변화에 따른 집중호우의 발생빈도와 강도가 증가하면서 대규모 홍수로 인한 인명 및 재산피해가 발생하고 있다. 그에 따라 홍수 상황을 신속하게 확보하고 홍수피해를 빠르게 예측하는 모니터링 기술이 필요하다. 최근 공간정보 분야에서 무인항공기 (UAV: Unmanned aerial vehicles)를 이용한 3차원 지형자료 확보 연구가 활발하게 이용되고 있다. 무인항공기는 지형자료 구축 뿐 만 아니라 홍수 시 신속한 홍수 모니터링이 가능하기 때문에, 본 연구에서는 무인항공기를 이용하여 홍수 전 지형자료 구축을 비롯하여, 홍수 시 모니터링, 홍수 후 지형자료 구축에 이르기까지 UAV를 이용한 홍수 모니터링 기술을 소개한다. 연구대상지는 금강 합류 직전 논산천 하류 1 km 지점으로, UAV를 이용한 지형자료를 구축하기 이전에 좌표 매칭을 위한 GCP (Ground Control Point ) 측량을 실시하고, UAV 비행계획을 수립하고 촬영한다. 촬영된 영상을 GCP좌표와 소프트웨어 (Pix4D)를 이용하여 정사영상과 DSM(Digital Surface Model)자료를 구축한다. 홍수시 UAV를 이용한 촬영을 통하여 동영상은 수재해 플랫폼에 송신하고, 이미지 영상은 홍수 전 영상처리와 동일한 방법을 이용하여 지형 자료를 구축하여, 홍수시 침수심이나 지형변화를 분석한다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.4
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• pp.303-310
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• 2020

This paper describes a Power Monitoring Unit (PMU) for Unmanned Aerial Vehicle (UAV) electrical system, It is designed for the PMU which performs data sensing of generator, transformer rectifier unit (TRU), battery and gear box installed in UAV and operate power ON/OFF devices of mission equipment. The PMU measures the voltage and current for the aircraft power source (generators, transformer rectifier unit and battery), measures the pressure and temperature of the gearbox, and performs the mission equipment power command received from the mission computer. The PMU was designed to meet the requirements of the UAV, and was performed through structure/thermal analysis, environmental test, EMI test and ground/flight tests.

• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.65-66
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• 2014

좁은지역에 대한 지형정보의 획득은 저고도 UAV시스템을 이용하는 것이 경제적이다. 최근 자동항법 UAV의 발전은 저고도 고해상도 영상을 원하는 주기로 얻을 수 있어 많은 분야에 응용하고 있다. 이러한 UAV시스템은 지상관제센터와 비행체 간의 긴밀한 통신이 이루어져야 하며 촬영 중 영상의 획득 여부를 모니터링할 수 있어야 한다. 본 연구에서는 NASA가 개발한 Worldwind를 커스터마이징하여 실시간 영상획득 모니터링 s/w를 개발하였다. 또한 개발시스템을 이용하여 정사영상 모자익을 실시하였으며 이에대한 정확도 분석을 실시하였다. 분석결과 검사점에 대해 정사모자익영상의 수평위치 정확도를 분석한 결과 X좌표에서 평균 0.181m, Y좌표에서 평균 0.203m의 편차를 보임으로써 1:1,000~5,000축척의 수치지도제작이 가능할 것으로 판단된다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.384-385
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• 2016

본 연구에서는 최근 어류 폐사, 상수원 오염 등의 피해를 발생시키고 있는 녹조를 대상으로 위성영상을 이용한 발생 유무와 분포를 분석하고자 하였다. 녹조는 엽록소를 가지고 광합성을 하므로 식생과 매우 유사한 분광특성을 가진다. 이는 위성영상에서 제공하는 근적외 정보로부터 정규식생지수를 산출하고 그 변화를 분석함으로써 녹조 발생 유무를 식별해낼 수 있음을 의미한다. 연구 대상지역인 대청호는 올해 첫 조류경보가 발령된 수역으로 8월~10월 사이 상류지역을 중심으로 녹조가 발생하였다. 본 연구에서는 Landsat-8 위성영상을 이용하여 대청호에서 발생한 녹조분포를 분석하고, 그 중 높은 농도의 녹조가 발생한 추소리를 직접 방문하여 Unmanned Aerial Vehicle(UAV) 자료를 취득하였다. UAV 촬영 영상을 통해 추소리 수역에 녹조가 다량 발생한 것을 확인할 수 있었다. 향후에는 고해상도 위성영상인 플래닛스코프 위성영상을 추가적으로 활용함으로써 녹조 모니터링의 정확성과 적시성을 확보할 예정이다.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.3
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• pp.302-309
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• 2020

Early-detection and monitoring of toxic chemical gas cloud with chemical detector is essential for reducing the number of casualties. Conventional method for chemical detection and reconnaissance has the limitation in approaching to chemically contaminated site and prompt understanding for the situation. Stand-off detector can detect and identify the chemical gas at a long distance but it cannot know exact distance and position. Chemical detection UAV is an emerging platform for its high mobility and operation safety. In this study, we have conducted chemical gas cloud detection with the stand-off chemical detector and the chemical detection UAV. DMMP vapor was generated in the area where the cloud can be detected through the field of view(FOV) of stand-off chemical detector. Monitoring the vapor cloud with standoff detector, the chemical detection UAV moved back and forth at the area DMMP vapor being generated to detect the chemical contamination. The hybrid detection system with standoff cloud detection and point detection by chemical sensors with UAV seems to be very efficient as a new concept of chemical detection.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.8-19
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• 2023

This paper presents advancement in multi- unmanned aerial vehicle (UAV) cooperative area surveillance, focusing on optimizing UAV route planning through the application of genetic algorithms. Addressing the complexities of comprehensive coverage, two real-time dynamic path planning methods are introduced, leveraging genetic algorithms to enhance surveillance efficiency while accounting for flight constraints. These methodologies adapt multi-UAV routes by encoding turning angles and employing coverage-driven fitness functions, facilitating real-time monitoring optimization. The paper introduces a novel path planning model for scenarios where UAVs navigate collaboratively without predetermined destinations during regional surveillance. Empirical evaluations confirm the effectiveness of the proposed methods, showcasing improved coverage and heightened efficiency in multi-UAV path planning. Furthermore, we introduce innovative optimization strategies, (Foresightedness and Multi-step) offering distinct trade-offs between solution quality and computational time. This research contributes innovative solutions to the intricate challenges of cooperative area surveillance, showcasing the transformative potential of genetic algorithms in multi-UAV technology. By enabling smarter route planning, these methods underscore the feasibility of more efficient, adaptable, and intelligent cooperative surveillance missions.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.393-406
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• 2018

Every year in the ocean, various accidents occur frequently and illegal fishing is rampant. Moreover, their size and frequency are also increasing. In order to reduce losses of life or property caused by these, it is necessary to have a means to perform remote monitoring quickly. As an effective platform of such monitoring means, an Unmanned Aerial Vehicle (UAV) is receiving the spotlight. In these situations where marine accidents or illegal fishing occur, main targets of monitoring are ships. In this study, we propose a UAV based ship monitoring system and suggest a method of determining ship positions using UAV multi-sensory data. In the proposed method, firstly, the position and attitude of individual images are determined by using the pre-performed system calibration results and GPS/INS data obtained at the time when images were acquired. In addition, after the ship being detected automatically or semi-automatically from the individual images, the absolute coordinates of the detected ships are determined. The proposed method was applied to actual data measured at 200 m, 350 m, and 500 m altitude, the ship position can be determined with accuracy of 4.068 m, 8.916 m, and 13.734 m, respectively. According to the minimum standard of a hydrographical survey, the ship positioning results of 200 m and 350 m data satisfy grade S and the results of 500 m data do grade 1a, where the accuracy is required for positioning the coastline and topography less significant to navigation order. Therefore, it is expected that the proposed method can be effectively used for various purposes of marine monitoring or surveying.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.535-544
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• 2017

In this paper, to overcome the limitation of information transmission and reception according to the RF system of UAV, it is necessary to check the position of many UAVs in flight on the basis of mobile communication and to make the LTE modem lightweight and low power And UAVs that are in operation are received and controlled. Through this study, we proposed a method to control real-time location tracking by connecting high-resolution images to the network anytime and anywhere. For this purpose, we propose the requirements and requirements of LTE modem using real-time high-speed data communication technology (3G, 4G LTE, Bluetooth) by presenting the communication module system of LTE-based UAV. N:N control system concept and implementation technology(Control system structure, control data flow chart, flight planning and transmission, real-time location tracking).