• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.05a
• /
• pp.271-276
• /
• 2009

An local area weather condition monitoring system to minimize many disasters from the sudden change of weather condition in local and mountain area is proposed. Firstly, the comparison of present state of the related monitoring systems and the possibility of realization with some merits are investigated. Moreover, this paper present direction of local area weather condition monitoring system based on integration of wireless sensor network and CDMA network following some case study. Through the efficient integration of both networks, the measured weather condition data from sensors can be transmitted to the server or mobile to monitor with high reliability. The proposed monitoring system will guide new type of project in wireless sensor network and support alarm service of the sudden change of weather condition to mobile user from central official regulations.

• Proceedings of the KSRS Conference
• /
• 2000.04a
• /
• pp.1-1
• /
• 2000

아리랑위성 1호는 1999년 12월 21일 미국 캘리포니아 반덴버그 공군기지에서 성공적으로 발사되어 초기 고도 702.5km, 궤도경사각 98.26도의 궤도 진입에 성공하였다. 발사 후 2 개월간의 초기 운용기간 (Launch Early Operation Phase) 동안 위성체의 점검 및 기본 기능시험이 완료되었고 현재 위성은 정상 임무궤도에서 운용되고 있다. 초기 운용기간에 위성에 탑재된 관측센서의 기능분석 및 시험 영상 촬영도 이루어졌다. 본 발표에서는 초기 운용기간에 전자광학카메라 (EOC)와 해석관측센서 (OSMI)로부터 획득한 영상자료의 일부를 공개한다. 이를 통해 향후 국토이용관리, 해양 및 기상 등 다 방면에 활용될 EOC 및 OSMI 자료의 현재 수신상황을 설명하고 영상자료에 대한 이해를 도모하고자 한다.

• Journal of Digital Contents Society
• /
• v.18 no.7
• /
• pp.1377-1386
• /
• 2017

We propose a smart ocean meteorological observation system which is capable of real-time measurement of vulnerable marine climate and oceanographic conditions. Besides, imported products have several disadvantages such that they can't be measured for a long time and can't transmit data in real time. In the proposed system, smart ocean observation digging system, it observes real-time ocean weather with data logger methods. Furthermore, we also use existing dataloggers functions with various sensors which are available in the ocean at the same time. Also, we applied the Kalman-filter algorithm to the ocean crest measurement to reduce the noise and increase the accuracy of the real-time wave height measurement. In the experiment, we experimented the proposed system with our proposed algorithms through calibration devices in the real ocean environment. Then we compared the proposed system with and without the algorithms. As a result, the system developed with a lithium iron phosphate battery that can be charged by a system used in the ocean and minimized power consumption by using an RTC based timer for optimal use. Besides, we obtained optimal battery usage and measured values through experiments based on the measurement cycle.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.5
• /
• pp.761-768
• /
• 2023

In the 4th Industrial Revolution, AI(Artificial Intelligence) and IoT(Internet of Things) technologies are being applied to across various fields, with particularly prominence in asset management, disaster management, and meteorological observation. In these fields, it is necessary to accurately determine the real-time and precise tracking of the object's location and status, and to collect various data even in situations that are difficult to detect with existing sensors. In order to address these demands, the use of GNSS(Global Navigation Satellite System) is essential, and this technology enables the efficient management of assets, disaster prevent and response, and accurate weather forecasting. In this paper, we provide the investigated results for the latest trends in the application of GNSS in the fields of asset management, disaster management, and weather observation, among various fields incorporating AI and IoT and analyze them.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.332-332
• /
• 2022

적설은 지구 기후시스템과 수문순환 과정에서 중요한 역할을 하고 있으며, 겨울철의 적설은 봄철에 녹으면서 식생과 수자원 제공에 큰 영향을 주는 인자로 알려져 있다. 동아시아가 위치한 북반구는 적설량의 90%가 관찰되고 토지의 약 42%가 긴 시간동안 눈으로 덮여 있어 지표 에너지와 물 균형에 영향을 주고, 특히 수자원 관리를 위한 유출이나 토양수분과 같은 수문 인자에 큰 영향을 미친다. 따라서 적설을 정확하게 예측하는 것은 수자원 관리에 있어 매우 중요한 일이다. 한편, 이러한 수문 순환을 정확히 예측하기 위해 수문 분야에서는 지면모형(Land Surface Model, LSM)을 많이 사용하고 있다. 지면모형은 지표면과 대기 사이의 상호작용을 모의하기 위해 개발되었고, 에너지, 수증기, 이산화탄소 등의 다양한 인자들의 교환에 대하여 해석하며, 토양수분, 유출량 등의 수자원 분야의 주요 인자들을 산출하여 수자원 관리에 적극적으로 활용되고 있다. 이에 본 연구에서는 National Center for Atmospheric Research(NCAR)에서 개발한 Community Land Model(CLM)을 사용하여 2001년부터 2016년까지 25km의 공간해상도로 동아시아 지역의 적설 모의를 평가하였다. CLM의 적설 모의 평가 인자는 Snow depth, Snow water equivalent의 2가지 인자를 대상으로 수행하였고, 모의 성능 평가를 위한 관측 자료로 NASA Aqua와 JAXA GCOM-W1 위성에 탑재된 Advanced Microwave Scanning Radiometer(AMSR) 센서에서 제공하는 위성 관측 자료와 Defense Meteorological Satellite Program(DMSP) 위성의 Special Sensor Microwave/Imager(SSM/I) 센서와 Nimbus-7 위성의 Scanning Multichannel Microwave Radiometer(SMMR) 센서에서 제공하는 위성 관측 자료를 기반으로 지상 기상 관측소 자료와 조합하여 재생성한 European Space Agency Global Snow Monitoring for Climate Research (ESA GlobSnow)의 자료를 사용하였다. 그 결과 CLM의 적설 모의는 과대 추정하는 것을 알 수 있었으며, 본 연구의 결과는 동아시아 적설 모의 개선을 위해 자료 동화를 사용하는 후속 연구의 기초자료로 사용할 수 있다.

• Proceedings of the Korean Society of Disaster Information Conference
• /
• 2017.11a
• /
• pp.278-279
• /
• 2017

북한 대부분이 미계측 지역으로서 자연재해 연구의 기초 데이터인 기상정보가 매우 부족한 실정이다. 이러한 지역은 천리안 기상위성 등 원격탐사 기술을 활용하여 재해 모니터링을 하여야한다. 천리안 기상위성은 기상청에서 운영하는 강우 알고리즘을 이용하면서 재해예측 보다는 일반적인 강우 예보에 중점을 두고 있다. 따라서 기상청 강우 알고리즘은 35 mm/hr를 초과하는 강우에 대해서는 탐지를 하지 못하므로 홍수위험 모니터링에 적합하지 않다. 본 연구에서는 이러한 문제를 해결하기 위해 기존의 천리안 강우강도 알고리즘에 GPM 위성 산출물(L3)과 같은 다중센서 자료를 적용하여 홍수유발 강우까지 측정할 수 있는 추정기술을 개발하였다. 개발된 강우 추정기술은 한국의 기상관측지점 94개소 자료와 비교 검증했을 때, 상관계수가 0.6 이상으로 기존의 알고리즘보다 개선된 강우를 추정할 수 있었다. 따라서 기존의 천리안 강우강도 알고리즘에서 추정하지 못했던 집중호우나 태풍의 강우강도를 정확하게 추정할 수 있으므로 미계측 지역의 홍수위험 모니터링에 도움이 될 것이다.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.34 no.9
• /
• pp.60-66
• /
• 2006

Now, on developing COMS(Communication, Ocean and Meteorological Satellite) has solar panel on the south panel only. Therefore, the wheel off-loading has to be performed periodically to reduce a induced momentum energy by a asymmetric solar panel. One of two East/West station keeping maneuver to correct simultaneously longitude and eccentricity, orbit corrections may be performed during one of the two wheel off-loading manoeuvres per day to get enough observation time for meteorological and ocean sensor. In this paper, we applied a linearized orbit maneuver equation to acquire maneuver time and delta-V. Nonlinear simulation for the station keeping is performed and compared with general station keeping strategy for fuel reduction.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.3
• /
• pp.467-472
• /
• 2022

The 3D ultrasonic anemometer transmits measured data by connecting PC and RS232C interface. Depending on the observation location, it is often necessary to extend the cable connecting the PC and the sensor. When installing on the test bed of the Air Meteorological Agency, the original AWM2919 cable was required to be extended because the distance between the PC container and the equipment installation site was more than 30 m. The cable was extended through a process such as extending the AWM2919 cable, converting the interface with the PC from RS232C to RS485, and testing the RS485 communication. After the equipment was installed with an extended cable, data were remotely collected and analyzed to confirm successful cable extension.

• Aerospace Engineering and Technology
• /
• v.5 no.2
• /
• pp.119-125
• /
• 2006

The first GEO satellite, COMS(Communication. Ocean & Meteorological Satellite) developed by Korean participants is a multi-functional satellite accommodating two observation payloads and a communication payload. Because of the inherent requirements given by these payloads, the physical layout of the instruments and sensors and of their electronics packages is critical to mission success. This technical paper presents an overview of the mechanical system design during the preliminary design phase and describes the design consideration to achieve the optimized performance.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.17 no.6
• /
• pp.121-132
• /
• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.