• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.1964-1970
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• 2010

A new intelligent power network (Smart Grid) that grafts some new technologies, such as the extension of the new and reproducible energy, electric motors, and electric storages, onto the regulation of green house gases according to the recent convention on climate changes has been actively promoted. As establishing such an intelligent power network, it is possible to implement a real-time rate system according to the change from the conventional single directional information transmission to the bidirectional information transmission. Such a real-time rate system can provide power during the chip rate hour by avoiding the high rate hour although customers use the same level of power through providing such real-time rate information including power generation costs. In this study, the establishment of an operating system that makes an effective use of the real-time rate system and its operation method are to be proposed.

• Journal of IKEEE
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• v.22 no.1
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• pp.53-60
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• 2018

Smart farm dissemination by continuously developing IoT is one of the best solution for decreasing labor in Korea farming area because of ageing. For this reason, the number of Smart farm in Korea is being increased. The Smart farm can control farming environment such as temperature for human. Specially, The important thing is controlling proper temperature for farming. In order to control the temperature, legacy smart farms are usually using pans or air conditioners which can control the temperature. However, those devices result in increasing production cost because the electric power consumption is high. For this reason, we propose a smart farm which can predict the proper temperature after an hour by using Deep learning to minimize the electric power consumption by controlling window instead of pans or air conditioners. We can see the 83% of electric power saving by means of the proposed smart farm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.603-604
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• 2017

In this paper, we propose system that automatically controlls greenhouse to make best environment to grow crops. The proposed system is consist of the function to automatically open and close water-roof, control the tublar well of groundwater and remote monitor information of greenhouse.

• Spatial Information Research
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• v.23 no.3
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• pp.67-77
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• 2015

This Study aimed to construction the plan of the statistics for national greenhouse gas inventories of international standards. Currently, the statistics of the greenhouse gas inventories of South Korea, has a problem that is not able to build the changed information. In previous studies, it has been limited to the construction of the information within each category. In order to solve these problems, targeting Gyeonggi province, we analyzed the land use change by utilizing the various information such as satellite images, KLIS, UPIS. As a result, we suggested the following implementation, classification system of LULUCF category, improvement of accuracy by utilizing satellite images of high resolution, additional research for methodology. Based on these contents, we suggested the construction plan of the statistics for national greenhouse gas inventories(LULUCF sector). Frist, it is necessary to construct of land use change informations for the past 20 years, Then, it need to create the matrix of land use change by utilizing satellite images and various land information systems.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.695-702
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• 2020

Recently, as research on smart farms has been actively conducted, indoor environment control, such as a green house, has reached a high level. However, In the field of forestry where cultivation is carried out in outdoor, the use of ICT is still insufficient. In this paper, we propose LPWA-based forest growth environment collection and big data analysis system using ICT technology. The proposed system collects and transmits the field cultivation environment data to the server using small solar power generation and LPWA technology based on the oneM2M architecture. The transmitted data is constructed as big data on the server and utilizes it to predict the production and quality of forest products. The proposed system is expected to contribute to the production of low-cost, high-quality crops through the fusion of renewable energy and smart farms. In addition, it can be applied to other industrial fields that utilize the oneM2M architecture and monitoring the growth environment of agricultural crops in the field.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.5
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• pp.193-199
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• 2015

Recently the artificial intelligence green house system, which collects automatically the informations of plants cultivation circumstances and controls the growing circumstances, is studied using temperature, humidity and illuminance sensors. In this paper, the inference for plants cultivation of optimum circumstance conditions is simulated on the internet bases by predicting the temperature, humidity and illuminance. On the IOT circumstances, the plant cultivation conditions of temperature, humidity and illuminance, using Arduino sensor, are transmitted to the manager on realtime and if the optimum condition of temperature and humidity for plant cultivation is not equal to the values, the system transmits automatically the SMS warning messages on realtime. Although the sudden climite conditions(snow, rain, hot weather) are occurred, the optimum condition of plant cultivation can be controlled. In this paper, using Fuzzy rules and WEKA TOOL, although the same flora temperature zone is used, the simulation is produced for the optimum value of temperature, humidity and illuminance for the zone.