• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.177-187
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• 2010

A MTG (Multimode Tracking and Guidance) system is employed to compensate for the limitations of individual seekers such as RF (Radio frequency) or IIR (Imaging Infra-red) and to improve the overall tracking and guidance performance in jamming, clutter, and adverse weather environments. In the MTG system, tracking filter, data association, and data fusion methods are important elements to maximize the effectiveness of precision homing missile guidance. This paper proposes the formulation of a Kalman filter for the estimation of line-of-sight rate from seeker measurements in missiles guided by proportional navigation. Also, we suggest the HPDA (Highest Probability Data Association) and data fusion methods of the MTG system for target tracking in the adverse environments. Mont-Carlo simulation is employed to evaluate the overall tracking performance and guidance accuracy.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.677-686
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• 2023

In this paper, we study the design and implementation of a smart home outing care system that recognizes the user's purpose of going out and delivers useful information that can help when going out. RSS service data of the Korea Meteorological Administration can be transmitted in real time using ESP8266, and a system that can provide weather information to users after analyzing the data using Arduino MEGA is implemented. Using App Inventor, you can pack the necessary items without forgetting, and you can change the settings according to the desired weather and purpose. The position of the microphone was placed outside to increase awareness by 12%, and the sensitivity of the pressure sensor was set to a maximum of 210 kΩ. If there is an obstacle between the doors, the doors open automatically. An ultrasonic sensor was placed on the ceiling of the drawer to recognize an object within the range of 0.5cm to 10cm to check the existence of an object, and a camera was installed to research a security reinforcement system.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.130-136
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• 2020

There are many problems that occur currently in agriculture industries. The problems such as unexpected of changing weather condition, lack of labor, dry soil were some of the reasons that may cause the growth of the plants. Condition of the weather in local area is inconsistent due to the global warming effect thus affecting the production of the crops. Furthermore, the loss of farm labor to urban manufacturing jobs is also the problem in this industry. Besides, the condition for the plant like air humidity, air temperature, air quality index, and soil moisture are not being recorded automatically which is more reason for the need of implementation system to monitor the data for future research and development of agriculture industry. As of this, we aim to provide a solution by developing IoT-based platform along with the irrigation for increasing crop quality and productivity in agriculture field. We aim to develop a smart garden system environment which the system is able to auto-monitoring the humidity and temperature of surroundings, air quality and soil moisture. The system also has the capability of automating the irrigation process by analyzing the moisture of soil and the climate condition (like raining). Besides, we aim to develop user-friendly system interface to monitor the data collected from the respective sensor. We adopt an open source hardware to implementation and evaluate this research.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.142-145
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• 2005

As SAR data have the strong point that is not influenced by weather or light amount compared with optical sensor data, they have high usfulness as temporary analysis fast and can be collected in case of like disaster. This study is to extract DEM from L-band data of JERS-1 SAR imagery using InSAR and DInSAR processing techniques. The accuracies of DEM extracted from the SAR data were evaluated by employing DEM derived from the digital topographic maps of 1:5000 scale as standard data.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.111-126
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• 2022

Land use and land cover (LULC) mapping is an important factor in geospatial analysis. Although highly precise ground-based LULC monitoring is possible, it is time consuming and costly. Conversely, because the synthetic aperture radar (SAR) sensor is an all-weather sensor with high resolution, it could replace field-based LULC monitoring systems with low cost and less time requirement. Thus, LULC is one of the major areas in SAR applications. We developed a LULC model using only KOMPSAT-5 single co-polarized data and digital elevation model (DEM) data. Twelve HH-polarized images and 18 VV-polarized images were collected, and two HH-polarized images and four VV-polarized images were selected for the model testing. To train the LULC model, we applied the conditional generative adversarial network (cGAN) method. We used U-Net combined with the residual unit (ResUNet) model to generate the cGAN method. When analyzing the training history at 1732 epochs, the ResUNet model showed a maximum overall accuracy (OA) of 93.89 and a Kappa coefficient of 0.91. The model exhibited high performance in the test datasets with an OA greater than 90. The model accurately distinguished water body areas and showed lower accuracy in wetlands than in the other LULC types. The effect of the DEM on the accuracy of LULC was analyzed. When assessing the accuracy with respect to the incidence angle, owing to the radar shadow caused by the side-looking system of the SAR sensor, the OA tended to decrease as the incidence angle increased. This study is the first to use only KOMPSAT-5 single co-polarized data and deep learning methods to demonstrate the possibility of high-performance LULC monitoring. This study contributes to Earth surface monitoring and the development of deep learning approaches using the KOMPSAT-5 data.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.21-30
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• 1999

The CLW (Cloud Liquid Water) is a parameter of vital interest in both modeling and forecasting weather. In mesoscale models, the magnitude of latent heat effects corresponds to the amount of CLW, which is important in the development of a certain weather system. The goal of this study is the estimation of CLW by GMS-5 data which is compared with that of SSM/I data and GMR(Grounded Microwave Radiometer)data. First of all, we found out the relationship of cloud albedo to cloud thickness, and caculated the CLW using the result of the relationship. The CLW amount of SSM/I or GMR and that of GMS-5 were compared, respectively. The correlation coefficient was about 0.86 and RMSE was 9.23 mg/$cm^2$ between GMS-5 data and GMR data. And also the correlation coefficient was 0.84 and RMSE was 14.02 mg/$cm^2$ between GMS-5 data and SSM/I data.

• Smart Structures and Systems
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• v.7 no.5
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• pp.349-363
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• 2011

To assess the performance of a structure requires the measurement of global and relative displacements at critical points across the structure. They should be obtained in real time and in all weather condition. A Global Navigation Satellite System (GNSS) could satisfy the last two requirements. The American Global Position System (GPS) provides long term acquisitions with sampling rates sufficient to track the displacement of long period structures. The accuracy is of the order of sub-centimetres. The steel building which hosts the authors' laboratory is the reference case-study within this paper. First a comparison of data collected by GPS sensor units with data recorded by tri-axial accelerometers is carried out when dynamic vibrations are induced in the structure by movements of the internal bridge-crane. The elaborations from the GPS position readings are then compared with the results obtained by a Finite Element (FE) numerical simulation. The purposes are: i) to realize a refinement of the structural parameters which characterize the building and ii) to outline a suitable way for processing GPS data toward structural monitoring.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.426-439
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• 2018

Purpose: To continuously monitor soil and climatic properties, a data acquisition system (DAQ) was developed and tested in plum farms (Gyewol-ri and Haechang-ri, Suncheon, Korea). Methods: The DAQ consisted of a Raspberry-Pi processor, a modem, and an ADC board with multiple sensors (soil moisture content (SEN0193), soil temperature (DS18B20), climatic temperature and humidity (DHT22), and rainfall gauge (TR-525M)). In the laboratory, various tests were conducted to calibrate SEN0193 at different soil moistures, soil temperatures, depths, and bulk densities. For performance comparison of the SEN0193 sensor, two commercial moisture sensors (SMS-BTA and WT-1000B) were tested in the field. The collected field data in Raspberry-Pi were transmitted and stored on a web server database through a commercial communications wireless network. Results: In laboratory tests, it was found that the SEN0193 sensor voltage reading increased significantly with an increase in soil bulk density. A linear calibration equation was developed between voltage and soil moisture content depending on the farm soil bulk density. In field tests, the SEN0193 sensor showed linearity (R = 0.76 and 0.73) between output voltage and moisture content; however, the other two sensors showed no linearity, indicating that site-specific calibration is important for accurate sensing. In the long-term monitoring results, it was observed that the measured climate temperature was almost the same as website information. Soil temperature information was higher than the values measured by DS18B20 during spring and summer. However, the local rainfall measured using TR 525M was significantly different from the values on the website. Conclusion: Based on the test results obtained using the developed monitoring system, it is thought that the measurement of various parameters using one device would be helpful in monitoring plum growth. Field data from the local farm monitoring system can be coupled with website information from the weather station and used more efficiently.

• Journal of the Korean Society of Hazard Mitigation
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• v.4 no.2 s.13
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• pp.61-69
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• 2004

Drought is one of the mai or environmental disasters. Weather data, particularity rainfall, are currently the primary source of information widely used for drought monitoring. However, weather data are often from a very sparse meteorological network. Therefore, data obtained from the Advanced Very High Resolution Radiometer(AVHRR) sensor boarded on the NOAA polar-orbiting satellites have been studied as a tool for drought monitoring. The normalized difference vegetation index(NDVI) and vegetation condition index(VCI) were used in this study. Also, a simple method to detect drought Is Proposed based on climatic water balance using NOAA/AVHRR data. The results clearly show that temporal and spatial characteristics of drought in Korea can be detected and mapped by the moisture index.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.93-96
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• 2015

In this paper, we introduce a fire detection system using context-aware sensor. In existing weather and based on vision sensor of fire detection system case, acquired image through sensor of camera is extracting features about fire range as processing to convert HSI(Hue, Saturation, Intensity) model HSI which is color space can have durability in illumination changes. However, in this case, until a fire occurs wide range of sensing a fire in a single camera sensor, it is difficult to detect the occurrence of a fire. Additionally, the fire detection in complex situations as well as difficult to separate continuous boundary is set for the required area is difficult. In this paper, we propose an algorithm for real-time by using a temperature sensor, humidity, Co2, the flame presence information acquired and comparing the data based on multiple conditions, analyze and determine the weighting according to fire it. In addition, it is possible to differential management to intensive fire detection is required zone dividing the state of fire.