• Journal of Bio-Environment Control
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• v.2 no.1
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• pp.69-76
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• 1993

최근 작물의 공장적 재배는 $\boxDr$식물공장$\boxUl$이라는 단어로 대표되는, 새로운 재배방식의 하나로서 세계적으로 주목받고 있다. 식물공장(plant factory or factory- style plant production system)이라는 단어의 의미와 같이 $\boxDr$시설내의 작물을 공장제품의 생산과 동일하게 재배하는 시스템$\boxUl$이다. 즉 자연환경에 의존하지 않고 인공환경하에서 식물을 공장적으로 재배하는 방식을 의미한다. 이를 위해서는 지하부의 양액, 지상부의 온습도, 탄산가스, 광 등에 대한 고도의 환경제어 및 작업의 자동화가 필요하다.(중략)

• Journal of Internet of Things and Convergence
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• v.3 no.1
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• pp.13-19
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• 2017

In this paper, we designed and implemented Thing Connected-Green, a self-installing agricultural automation system capable of remote monitoring and control based on Low Power Wide Area communication technology (LPWA). Farming requires water, sunlight, soil, fertilizer, temperature control, etc., and these elements can be remotely monitored and controlled using an automated system. Using this system, it is possible to construct an agricultural automation system which can be optimized according to the kind of plant and cultivation environment from vinyl house to flower garden. The information gathered from the sensor is stored in the server through the gateway, and the optimal cultivation environment can be set and operated using the smart phone based on the big data.

• Journal of Bio-Environment Control
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• v.25 no.1
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• pp.30-41
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• 2016

Korean government has planned to increase the productivity of horticultural crops and to expand supply smart greenhouse for energy saving by modernization of horticultural facilities based on ICT in policy. However, the diversity and linkages of monitoring and control are significantly insufficient in the agricultural sector in the current situation. Therefore, development of a service system with smart-farm based on the internet of things(IoT) for intelligent systemization of all the process of agricultural production through remote control using complex algorithm for diverse monitoring and control is required. In this study, domestic and international research trend related to ICT-based horticultural facilities was briefly introduced and limits were analyzed in the domestic application of the advanced technology. Finally, future core technologies feasible to graft in agricultural field were reviewed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.848-851
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• 2015

IT convergence with agriculture is expected to bring more efficiency and quality improvement in producing, distributing, consuming of agricultural products with the aid of information processing and autonomous control technologies of the IT area. In this paper, it is required to consider the actualized IT convergence case for agriculture, namely Smart Farming as a solution to cope the presented problems. In addition, suggest to standard functional model and standardization items for the smart farming based on network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.611-614
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• 2015

IT convergence with agriculture is expected to bring more efficiency and quality improvement in producing, distributing, consuming of agricultural products with the aid of information processing and autonomous control technologies of the IT area. In this paper, it is required to consider the actualized IT convergence case for agriculture, namely Smart Farming as a solution to cope the presented problems. In addition, suggest to ICT standardization road map for the smart farming based on network.

• Journal of the Korea Convergence Society
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• v.8 no.9
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• pp.339-345
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• 2017

Recently, agriculture and the environment has changed dramatically due to global warming and abnormal weather. In particular, it is necessary to develop new agricultural techniques according to transforming the growing environment of agricultural crops. Therefore, "Smart Farm" building technology for controlling agricultural environment and improving efficiency for ICT technology development has recently been introduced. However, in reality, systematic and objective evaluation items are absent at various levels and management levels that affect the management environment of the smart farm. In this research, it derived the importance index among the factors associated with Smart Farm technology by AHP method. As a result, in order to evaluate comprehensive operation and management of the smart farm, the two evaluation fields(sensor device and control/information management system) were selected as the top evaluation items. These results mean that system that can detect the growth environment information of agricultural crops and control the growing environment is more important than anything, when smart farm is applied. It is judged that the results of this research can be used as basic data for making evaluation indicators associated with the introduction of smart palm technology in the future.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.907-914
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• 2017

Recently, industrialization and automation for crops has enabled the development of smart farm technology over the world This is due to the need for the automation and convenience of the agricultural system to aging the population and reducing the labor force. In this system, the smart app can control the temperature and humidity that can be conveniently managed by the farmers. It is possible to check the status of the greenhouses in real time in the smartphone and maintain the optimum temperature and humidity, thereby helping to prevent pests and diseases, to grow crops, and to improve the labor force and productivity of farmers and fishermen.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.1
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• pp.77-83
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• 2011

This paper proposes a remote monitoring system, which manages crops' growth environment on a real-time basis by applying to greenhouses Green U-IT technology connecting environment control equipment such as temperature sensors, soil sensors, and moisture censors with computers. Information on greenhouses' environment is stored in a database, and by utilizing linear regression analysis and differential item functioning (DIF) analysis, optimal information on growth and environment is extracted from stored information in the form of items desired by users, and compared, analyzed, and monitored. By linking greenhouse environment control system with web environment and remotely controlling the system, users do not need to visit farmland and can remotely control greenhouses' environment on a real-time basis. Therefore farmhouses' production efficiency may be enhanced by continuously providing optimal growth environment for plants.

• Journal of Biosystems Engineering
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• v.24 no.5
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• pp.415-424
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• 1999

This study was conducted to assess performances of the developed environmental control systems under various seasons of Korea. In all trials for the environmental control systems, the manure pit ventilation system in the windowless pig-housing with partly slatted floor was used. Consequently, under all seasons of Korea, the complex environmental control systems could comfortably maintain the indoor temperature (14.8~27.2$^{\circ}C$) , concentrations of noxious gases (CO2 gas : 631~1,874ppm, NH3 gas : 0.3~3.2ppm), air velocity (0.11~0.23m/s), air movement, and so on. Therefore, the performances of the complex environmental control systems were evaluated as proper as the intended.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.563-566
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• 2017

In order to prevent livestock diseases and produce the high quality livestock products in the livestock industry, it is necessary to manage the conditions of the livestock farms in the optimal condition. Therefore, these days the research on livestock growth models that analyze the factors of the air environment, the breeding environment, and the numerical rules of livestock in vivo is being carried out to improve and manage the environment in which livestock are kept. However, conventional models of growth are not sufficient to support the decision-making to control complex environment in pen by analyzing and interpreting air environment and breeding environment in a complex way. In this paper, we propose a method to control the complex environment in pen by using artificial neural network model based on biological information, air environment, breeding environment and production information.