• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.65-69
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• 2008

This study is aimed to develope a remote control ship for acquisition of various underwater information. Remote control ship equipped with GPS, echosounder, sidescan sonar, subbottom profiler. Remote control ship is an automatic system for acquisition of inland water and coast information. For the development of remote control ship, underwater information acquisition of reservoir, dam, polluted area is expected. Also, multibeam echosounder, image sensor, water analysis sensor, etc. could be equipped in one ship. So robot-ship will be applied for the most part of industry managing water resources and preventing the flood by making bed topographic map and estimating water volumes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.533-536
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• 2016

In this paper, we take advantage of the SEN Remote HMI App as a tool based on Raspberry Pi server for the smart home control. This is a smart home control system built in an open and a low-cost Raspberry Pi as a server, and take advantage of Android-based graphical programming software SEN Remote HMI. If you build it based system expansion and additional works interface via the Raspberry Pi and Arduino, it is expected to be extended to the Internet of Things (IoT) enabling environment for the implementation of smart home.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1395-1397
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• 2003

This paper is concerned with a client-server architecture for the remote control of wind turbine system over the internet network. Recently the development of internet are study in remote area machine control, observation, remote control (teleoperation) automation industrial system in several fields. One of the important problems which should be solved in the remote control is an irregular time delay problem. This research practiced emergency system on-off experiment to Internet. Finally, we apply it to a wind turbine system that consists of a remote control and network via internet. It is experimented that real time of internet remote control and stability of wind turbine system.

• Journal of Biosystems Engineering
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• v.25 no.4
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• pp.301-310
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• 2000

An autonomous tractor system was developed and its performance was evaluated. The system consisted of a tractor system of and a remote control station. The tractor and the remote control station communicated each other via wireless modems. The tractor had a DGPS(differential global positioning system), sensors, a controller and a modem. The DGPS collected position data and the tractor status was estimated. The information of tractor status and sensors was transferred to the remote control station. Then, the control station determined the control data such as steering angles using a fuzzy controller. The fuzzy controller used the information from the DGPS, sensors, and GIS(geographic information system) data. The control data were obtained by remote signal processing at the control station The control data for autonomous operation were transferred to the tractor controller. The performances of an autonomous tractor were evaluated for various speeds, different initial positions and different initial headings. About 1.3 seconds of time lag was occurred in transferring the tractor status data and the control data. Compensation the time lag, about 27cm deviation was observed at the speed of 0.5m/s and 37cm at the speed of 1m/s. Error caused mainly by the time lag and it would be reduced by developing a full-duplex radio module for controlling the remote tractor.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.277-279
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• 2003

The study utilizes remote sensing as the main monitoring means. With different spatial high-resolution, multichannel ASTER remote sensing image as the main information in Beijing city zone; with regional border and statistical data as auxiliary factor a study between the thermal space distribution character and the underground medium is analyzed based on the GIS logical algorithm and synthetic analysis technology. Results show thermal forming mechanism and the rule of distribution is mainly related to the underground medium and the change of the city distribution. Different underground medium has different degree and intensity influence on the thermal space distribution. Furthermore, urban greenbelt and water areas can reduce the thermal effect and large-scale greenbelt creates green island effect. In addition, Road net, residential area, population density, heat resources and so on have some positive effect on the thermal distribution, which increase the local temperature and intensity on the other hand. It is important to study the thermal distribution and its related factors, which contributes to the plan, construction and development of the city.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.6
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• pp.703-709
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• 2019

This paper proposes a monitoring and remote control system, an essential part of In Vehicle Infotainment (IVI) and Human Vehicle Interface (HVI) to provide safety and convenience to a driver. The system utilizes Bluetooth for a short range communication and utilizes WCDMA for a long range communication to enhance efficiency. In this paper, an integrated controller, which integrates a CAN communication module, a Bluetooth communication module, a WCDMA communication module, is designed to control a car. Also, a remote server for managing data is designed to provide real-time monitoring and remote control for a user via smart devices. Experiment results show that all the proposed remote control, driving log, real-time monitoring, and diagnostics functions are working properly. With the proposed system, a driver can drive safely by monitoring and inspecting a car before driving via smart devices, and control conveniently by controlling a car remotely.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.367-372
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• 2006

Cloud detection algorithm is being developed as primary one of the 16 baseline products of CMDPS (COMS Meteorological Data Processing System), which is under development for the real-time application of data will be observed from COMS Meteorological Imager. For cloud detection from satellite data, we studied two different algorithms. One is threshold technique based algorithm, which is traditionally used, and another is artificial neural network model. MPEF scene analysis algorithm is the basic idea of threshold cloud detection algorithm, and some modifications are conducted for COMS. For the neural network, we selected MLP with back-propagation algorithm. Prototype software of each algorithm was completed and evaluated by using the MTSAT-IR and GOES-9 data. Currently the software codes are standardized using Fortran90 language. For the preparation as an operational algorithm, we will setup the validation strategy and tune up the algorithm continuously. This paper shows the outline of the two cloud detection algorithms and preliminary test results of both algorithms.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.153-162
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• 2004

In the summer of 1998-2001, a huge flood occurred in the Yangtze River in the eastern China. Low salinity water less than 28 psu from the river was detected around the southwestern part of the Jeju Island, which is located in the southern part of the Korean Peninsula. We studied how to detect low salinity water from the Yangtze River, that cause a terrible damage to the Korean fisheries. We established a relationships between low salinity at surface, turbid water from the Yangtze River and digital ocean color remotely sensed data of SeaWiFS sensor in the northern East China Sea, in the summer of 1998, 1999, 2000 and 2001. The salinity charts of the northern East China Sea were created by regeneration of the satellite ocean color data using the empirical formula from the relationships between in situ low salinity, in situ measured turbid water with transparency and SeaWiFS ocean color data (normalized water leaving radiance of 490 nm/555 nm).

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.21-32
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• 2007

Fire fuel map is one of the most critical factors for planning and managing the fire hazard and risk. However, fuel mapping is extremely difficult because fuel properties vary at spatial scales, change depending on the seasonal situations and are affected by the surrounding environment. Remote sensing has potential to reduce the uncertainty in mapping fuels and offers the best approach for improving our abilities. Especially, Hyperspectral sensor have a great potential for mapping vegetation properties because of their high spectral resolution. The objective of this paper is to evaluate the potential of mapping fuel properties using Hyperion hyperspectral remote sensing data acquired in April, 2002. Fuel properties are divided into four broad categories: 1) fuel moisture, 2) fuel green live biomass, 3) fuel condition and 4) fuel types. Fuel moisture and fuel green biomass were assessed using canopy moisture, derived from the expression of liquid water in the reflectance spectrum of plants. Fuel condition was assessed using endmember fractions from spectral mixture analysis (SMA). Fuel types were classified by fuel models based on the results of SMA. Although Hyperion imagery included a lot of sensor noise and poor performance in liquid water band, the overall results showed that Hyperion imagery have good potential for wildfire fuel mapping.

• Journal of the Korean earth science society
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• v.40 no.4
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• pp.329-339
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• 2019

Arctic warming is a global issue. The sea ice in the Arctic plays a crucial role in the climate system. We thought that a recent abnormality in many countries in the northern hemisphere could be related to the effects of shrinking sea ice in the Arctic. Many research groups monitor sea ice in the Arctic for climate research. Satellite remote sensing is an integral part of Arctic sea ice research due to the Arctic's large size, making it difficult to observe with general research equipment, and its extreme environment that is difficult for humans to access. Along with monitoring recent weather changes, Korea scientists are conducting polar remote sensing using a Korean satellite series to actively cope with environmental changes in the Arctic. The Korean satellite series is known as KOMPSAT (Korea Multi-Purpose Satellite, Korean name is Arirang) series, and it carries optical and imaging radar. Since the organization of the Satellite Remote Sensing and Cryosphere Information Center in Korea in 2016, Korean research on and monitoring of Arctic sea ice has accelerated rapidly. Moreover, a community of researchers studying Arctic sea ice by satellite remote sensing increased in Korea. In this article, we review advances in Korea's remote sensing research for the polar cryosphere over the last several years. In addition to satellite remote sensing, interdisciplinary studies are needed to resolve the current limitations on research on climate change.