• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.192-207
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• 2020

Profitability of upland crops is better than paddy crops and proportion of upland is increasing. However, there is a lack of infrastructures for upland irrigation. The object of this study were to develop water supply scenarios using individual and collective agricultural wells to evaluate economic feasibility to consider geographical analysis of upland farms and water supply facilities. Cheongyang, Dangjin, Yesan, and Goesan were selected as study areas where four different crops of red pepper, chinese cabbage, apple, and bean, respectively, were mainly produced in Chungcheong province. As a result, B/C ratio was estimated as 1.49, 1.36, 1.90, and 0.71 in using individual wells scenario, and 1.45, 1.20, 1.91, and 0.65 in using collective wells scenario for red pepper, chinese cabbage, apple, and bean. It turned out that change of price effected on economic feasibility a lot for crops with low production income. As a result of evaluating economic feasibility by number of plots for developing collective well, there was no effect of economy of scale for red pepper and chinese cabbage. In case of collectivizating more than 20 upland plots, effect of economy of scale appeared for apple and bean. In conclusion, development of water using high value crops including red pepper and apple, and effect of collective well requires additory analysis of .spatial distribution of farms.

• Journal of Bio-Environment Control
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• v.27 no.2
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• pp.147-157
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• 2018

With the rapid development of the 4th industrial revolution, the large-sized facilities of agriculture have been developed with high-technologies. However, it is difficult to maintain the optimum environment in large-sized facilities. Although it is essential to control micro-climate properly in large-sized facilities, there are a lot of problems to utilize high-technologies and equipment because of insufficient education for farmers. Most farms have limitations to access to their farm because of prevention of epidemics, exposure of management know-how, and so on. Especially, it is difficult to understand internal environmental factors (airflow, temperature, humidity, etc.) for farmers because these factors are invisible. Recently, Virtual reality technology which allows users to experience various phenomena directly is attracting attention. Virtual reality is very useful technology to visualize airflow and temperature distribution and so on. However, there is no cases applied this technology to agricultural facilities. In this study, research trends of virtual reality in various fields were investigated. In particular, the limitation and possibility of virtual reality technology were analyzed for educating farmers. Finally, the development of virtual reality contents for smart-farm facility were suggested.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.320-331
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• 2013

The National Center for AgroMeteorology (NCAM) has designed a risk management solution for individual farms threatened by the climate change and variability. The new service produces weather risk indices tailored to the crop species and phenology by using site-specific weather forecasts and analysis derived from digital products of the Korea Meteorological Administration (KMA). If the risk is high enough to cause any damage to the crops, agrometeorological warnings or watches are delivered to the growers' cellular phones with relevant countermeasures to help protect their crops against the potential damage. Core techniques such as scaling down of weather data to individual farm level and the crop specific risk assessment for operational service were developed and integrated into a cloud based service system. The system was employed and implemented in a rural catchment of 50 $km^2$ with diverse agricultural activities and 230 volunteer farmers are participating in this project to get the user-specific weather information from and to feed their evaluations back to NCAM. The experience obtained through this project will be useful in planning and developing the nation-wide early warning service in agricultural sector exposed to the climate and weather extremes under climate change and climate variability.

• Journal of agriculture & life science
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• v.46 no.5
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• pp.137-141
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• 2012

The foot and mouth disease(FMD) was occurred from Andong city on November 23, 2010 and spread out the whole country except Jeju island and Jeolla-do. About 3.4 million livestock such as cow and pig was buired at 4,200 sites during preventive measures of FMD. Government did not effectively respond to the FMD crisis management so FMD spread out the whole country. To Prevent the spread FMD, Farms have to fast approaching and respond directly to smartphones and Tablet PC applications. Resolve the difficulties of using smart devices and easy to operate for the effective utilization of the development of simple applications. This application of FMD, developed for the prevention and alarm applications, foot and mouth disease will be caused, farmers around the farm in case of risk and the seriousness of the FMD will notify smartphone, FMD prevent additional damage due to be interested in preventing further that allows your application is for development purposes.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.107-119
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• 2019

As the development of ICT and integration technology, many changes and innovations in agriculture field are implemented. The agricultural sector has shifted from a traditional industry to a new industrial form called the 6th industry combined with various advanced technologies such as ICT and IT. Various approaches have been attempted to analyze and predict crops based on spatial information. In particular, a variety of research has been carried out recently for crop cultivation and smart farms using drones. The goal of this study was to establish an agricultural drought monitoring system using drones to produce scientific and objective indicators of drought. A soil moisture sensor was installed in the drought area and checked the actual soil moisture. The soil moisture data was used by the reference value to compare and analyze the temperature and NDVI established by drones. The soil temperature by the drone thermal image sensor and the NDVI by the drone hyperspectral was analyzed the correlation between crop condition and soil moisture in study area. To verify this, the actual soil moisture was calculated using the soil moisture measurement sensor installed in the target area and compared with the drone performance. This study using drone drought monitoring system may enhance to promote the crop data and to save time and economy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.156-162
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• 2021

The number of smart farms has increased to save labor in agricultural production as the subsidy become available from central and local governments. The number of illegal greenhouses has also increased, which causes serious issues for the local governments. In the present study, we developed Mask-RCNN model to detect greenhouses based on satellite images. Greenhouses in the satellite images were labeled for training and validation of the model. The Mask-RC NN model had the average precision (AP) of 75.6%. The average precision values for 50% and 75% of overlapping area were 91.1% and 81.8%, respectively. This results indicated that the Mask-RC NN model would be useful to detect the greenhouses recently built without proper permission using a periodical screening procedure based on satellite images. Furthermore, the model can be connected with GIS to establish unified management system for greenhouses. It can also be applied to the statistical analysis of the number and total area of greenhouses.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.857-862
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• 2021

Recently, rapid climate change has had a significant impact on the bee ecosystem. The decrease in the number of bees and the change in the flowering period have a huge impact on the harvesting of beekeepers. Accordingly, attention is focused on smart beekeeping, which introduces IoT technology to beekeeping. According to the characteristics of beekeeping, it is impossible to continuously observe the beehive in the hive with the naked eye, and the condition of the hive is mostly dependent on knowledge from experience. Although a system that can measure partly through sensors such as temperature/humidity change inside the hive and measurement of the amount of CO2 is applied, there is no research on measuring the movement path and amount of movement of bees inside the beehive. Part of the migration of honeybees inside the hive can provide basic information to predict the most important cleavage time in beekeeping. In this study, we propose a device that detects the movement path of bees and measures and records data entering and exiting the hive in real time. The device proposed in this study was developed according to the honeycomb standard of the existing beehive so that beekeeping farms could use it. The development method used a photodetector that can detect the movement of bees to configure 16 movement paths and to detect the movement of bees in real time. If the measured honeybee movement status is utilized, the problem of directly observing the colony with the naked eye in order not to miss the swarming time can be solved.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1145-1156
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• 2022

In order to effectively secure site suitability for the development of large-scale offshore wind farms, it is essential to minimize the environmental impact of development and analyze the conflicts of benefit between social, ecological, and economic core values. In addition, a preliminary review of site adequacy must be preceded in order not to collide with other used areas in the marine spatial plan. In addition, it is necessary to conduct local meteorological characteristics analysis including wind resources near Jeollanam-do area before project feasibility study. Therefore, wind resource analysis was performed using the observation data of the meteorological mast installed in Wangdeungnyeo near Anmado, Yeonggwang, and the optimal site was selected after excluding geographical constraints related to the location of the offshore wind farm. In addition, the annual energy production was calculated by deriving the optimal wind farm arrangement results suitable for the local wind resources characteristics based on WindSim SW, and it is intended to be used as basic research data for site discovery and selection of suitable sites for future offshore wind farm projects.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.265-278
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• 2022

The global energy paradigm is rapidly changing by centering on carbon neutrality, and wind energy is positioning itself as a leader in renewable energy-based power sources. The success of onshore and offshore wind energy projects focuses on securing the economic feasibility of the project, which depends on securing high-quality wind resources and optimal arrangement of wind turbines. In the process of constructing the wind farm, the optimal arrangement method of wind turbines considering the main wind direction is important, and this is related to minimizing the wake effect caused by the fluid passing through the structure located on the windward side. The accuracy of the predictability of the wake effect is determined by the wake model and modeling technique that can properly simulate it. Therefore, in this paper, using WindSim, a commercial CFD model, the wake diffusion pattern is analyzed through the sensitivity study of each wake model of the proposed onshore wind farm located in the mountainous complex terrain in South Korea, and it is intended to be used as basic research data for wind energy projects in complex terrain in the future.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.861-866
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• 2023

Unlike conventional smart farms that require chemical fertilizers and large spaces, aquaponics farming, which utilizes the symbiotic relationship between aquatic organisms and crops to grow crops even in abnormal environments such as environmental pollution and climate change, is being actively researched. Different crops require different environments and nutrients for growth, so it is necessary to configure the ratio of aquatic organisms optimized for crop growth. This study proposes a method to measure the degree of growth based on area and volume using image processing techniques in an aquaponics environment. Tilapia, carp, catfish, and lettuce crops, which are aquatic organisms that produce organic matter through excrement, were tested in an aquaponics environment. Through 2D and 3D image analysis of lettuce and real-time data analysis, the growth degree was evaluated using the area and volume information of lettuce. The results of the experiment proved that it is possible to manage cultivation by utilizing the area and volume information of lettuce. It is expected that it will be possible to provide production prediction services to farmers by utilizing aquatic life and growth information. It will also be a starting point for solving problems in the changing agricultural environment.