• Title/Summary/Keyword: 스마트 농업

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A Scenario-based Approach in Smart Agriculture Services (스마트농업 서비스의 시나리오 기반 접근)

  • Lee, Soong-Hee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.7
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    • pp.1705-1710
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    • 2015
  • There have been lots of researches and developments for smart agriculture that enables higher efficiency and productivity by applying ICT into the agriculture field recently. However, there still remain many difficulties in purchasing foreign equipments or overseas expansion due to lack of international standards that are internationally approved. Such necessity leads to the international standardization activities driven by domestic experts especially in ITU-T SG13. This paper presents several smart agriculture services based on the service approach that can effectively describe use cases. The proposed architecture of service provision was applied to the document that has been consented as the ITU-T Recommendation Y.2238.

Agriculture Bigdata Management and AI Research Platform Development (농업 빅데이터 관리 및 인공지능 연구 플랫폼 개발)

  • Kim, Ki-Hyeon;Seok, Woojin;Moon, Junghoon;Kim, Kwangsoo;Sim, Joonyong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.11a
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    • pp.507-509
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    • 2022
  • 농업은 우리의 삶에서 빼놓을 수 없는 중요한 분야이며, 농업은 토지를 이용하여 다양한 작물들을 길러 음식을 만드는 기본이라고 말할 수 있다. 이렇게 중요한 농업 분야를 ICT 분야에서 가장 이슈가 되는 기술인 인공지능 기술과 결합하여 스마트팜과 같은 농업의 디지털화를 구축할 수 있다. 이와 같은 스마트팜 구축을 위해서는 기본적으로 다양한 작물의 빅데이터를 제공하고, 이 데이터를 바탕으로 인공지능을 수행하여 다양한 결과를 제공할 수 있다. 하지만 인공지능 연구를 수행하기 위한 시스템 및 플랫폼의 부재라는 문제점이 존재한다. 이러한 문제점을 해결하기 위해 농업 빅데이터 관리 및 인공지능 연구 플랫폼 개발을 위한 과제를 통해 농업 빅데이터를 관리하고 인공지능을 연구자들이 손쉽게 수행할 수 있는 플랫폼을 개발하여 농업 분야의 작물 생산성 향상에 기여하고자 한다.

A Model Study for Development of Evaluation Criteria for Smart Farm Horticultural (시설원예 스마트 팜 평가 기준 개발을 위한 모델 연구)

  • Kim, Tae-Hyeong;Kim, Dae Ho
    • 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.

Smart Plant Disease Management Using Agrometeorological Big Data (농업기상 빅데이터를 활용한 스마트 식물병 관리)

  • Kim, Kwang-Hyung;Lee, Junhyuk
    • Research in Plant Disease
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    • v.26 no.3
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    • pp.121-133
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    • 2020
  • Climate change, increased extreme weather and climate events, and rapidly changing socio-economic environment threaten agriculture and thus food security of our society. Therefore, it is urgent to shift from conventional farming to smart agriculture using big data and artificial intelligence to secure sustainable growth. In order to efficiently manage plant diseases through smart agriculture, agricultural big data that can be utilized with various advanced technologies must be secured first. In this review, we will first learn about agrometeorological big data consisted of meteorological, environmental, and agricultural data that the plant pathology communities can contribute for smart plant disease management. We will then present each sequential components of the smart plant disease management, which are prediction, monitoring and diagnosis, control, prevention and risk management of plant diseases. This review will give us an appraisal of where we are at the moment, what has been prepared so far, what is lacking, and how to move forward for the preparation of smart plant disease management.

An Environment Information Management System for Cultivation in Agricultural Facilities using Augmented Reality (증강현실 기반 농업용 환경 정보 관리 시스템)

  • Kim, Min-ji;Kim, Jong-Ho;Koh, Jin-Gwang;Lee, Sung-Keun;Lee, Jae-Hak
    • The Journal of Bigdata
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    • v.3 no.2
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    • pp.113-121
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    • 2018
  • In this study, an augmented reality(AR)-based information management system for agricultural facility is proposed. Using a variety of sensed data transmitted by Lora-based wireless networks deployed at the agricultural facility, this system is capable of augmenting the sensed data and displaying them on the user's smartphone screen to provide visualized information to user. When users point their smartphone camera to the agricultural facility, the environment information collected from numerous sensors installed at the facility would be visualized and appear on the screen. Unlike traditional system which requires user to search a specific facility and then select sensor(s) to obtain the environment information, the proposed system shows the information on smartphone screen by augmenting it with real image captured by camera without doing a series of time-taking selection process. Since the way of acquiring information is through image or video, this system contributes to convenient monitoring and efficient management for agricultural facility.

Standard Functional Model and Standardization items for Smart Farming (스마트 농업을 위한 표준 기능 모델과 표준화 항목)

  • Kim, Dong il;Chung, hee Chang
    • 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.

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High-efficiency Agricultural Heater and Smart Control System Utilizing Heat Pipe (히트파이프를 활용한 농업용 고효율난방기 및 스마트 제어시스템)

  • Kim, Eung-Kon;Lim, Chang-Gyoon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.6
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    • pp.1151-1158
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    • 2017
  • The Effluent Heat Pipe integral with the heater is a device that recreates unused thermal energy from the plant in winter, and thus reuses unused energy before releasing the exhaust heat. Through the establishment of facility horticulture and glass greenhouses, we identified the problems of our agricultural heaters, and we proposed efficient agricultural efficiency and smart control systems for optimum agricultural efficiency and smart house.

ICT Standardization Road map for Smart Farming (스마트 농업을 위한 ICT 표준화 로드맵)

  • Kim, Dong il;Chung, Hee Chang;Moon, Ae Kyung
    • 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.

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