• Journal of Korean Library and Information Science Society
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• v.34 no.1
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• pp.239-260
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• 2003

The purpose of this study is to devise a classification scheme to arrange the agricultural information efficiently. In the first part it defines the agricultural science and studies the content and system of the agricultural science. It compares current KDC with DDC, UDC and NDC used to agriculture parts, and it studies AGRICOLA SCC. On the basis of it, this study is displayed the new classification for the agricultural science. The new classification scheme Is classified by the basic theories related to agriculture, agriculture of plants, animal agriculture, food products, and auxiliary disciplines in turn. The number of main divisions are set up 23 items.

• Agribusiness and Information Management
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• v.7 no.2
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• pp.12-18
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• 2015

Since 2000s, proper utilization of IoT (Internet of Things) technology is a key factor for a firm to become more competitive, and this stream is not exceptional for the food and agriculture industry. Along with this stream, Korea government organization, for example MAFRA (Ministry of Agriculture, Food and Rural Affairs), elected to adopt IoT technology, such as USN and RFID technologies, in the food and agriculture industry. Based on the IoT technology, MAFARA launched six "IoT based farm" project in 2007. IoT based farm project includes IoT based greenhouse system project, and it shows drastic efficiency in terms of cost reduction. When it comes to the productivity, however, the effect of IoT based greenhouse system is still ambiguous. In this regard, this study conducted systems analysis and design for IoT based tomato greenhouse in order to help farmers' decision making related to the productivity by establishing standardized database structure and designing output form to analyze productivity indices. Proposed systems analysis and design can be utilized as a data analysis tools by farmers. Productivity data from the proposed systems is can be used by researchers to identify the relationship among environment, plant growth and productivity. Policy makers also can refer to the data and output forms to predict the quantity of fruit during certain period and to revise production guideline more precisely.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.217-224
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• 2019

As the world's population grows, how to maintain the food supply is becoming a bigger problem. Now and in the future, big data will play a major role in decision making in the agriculture industry. The challenge is how to obtain valuable information to help us make future decisions. Big data helps us to see history clearer, to obtain hidden values, and make the right decisions for the government and farmers. To contribute to solving this challenge, we developed the Agriculture Big Data Analysis System. The system consists of agricultural big data collection, big data analysis, and big data visualization. First, we collected structured data like price, climate, yield, etc., and unstructured data, such as news, blogs, TV programs, etc. Using the data that we collected, we implement prediction algorithms like ARIMA, Decision Tree, LDA, and LSTM to show the results in data visualizations.

• Journal of Power Electronics
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• v.7 no.4
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• pp.286-293
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• 2007

This paper proposes a distribution voltage control method when a voltage increase condition occurs due to reverse power flow from the clustered photovoltaic (PV) system. This proposed distribution voltage control is performed a by distribution-unified power flow controller (D-UPFC). D-UPFC consists of a hi-directional ac-ac converter and transformer. It does not use any energy storage component or rectifier circuit, but it directly converts ac to ac. The distribution model and D-UPFC voltage control using the ATP-EMTP program were simulated and the results show the voltage increase control in the distribution system.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.261-265
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• 2004

The purpose of this study is to present a standardized scheme for providing agriculture-related information at various spatial resolutions of satellite images including Landsat＋ETM, KOMPSAT-1 EOC, ASTER VNIR, and IKONOS panchromatic and multi-spectral images. The satellite images were interpreted especially for identifying agricultural areas, crop types, agricultural facilities and structures. The results were compared with the land cover/land use classification system suggested by Ministry of Construction & Transportation based on NGIS (National Geographic Information System) and Ministry of Environment based on satellite remote sensing data. As a result, high-resolution agricultural land cover map from IKONOS imageries was made out. The results by IKONOS image will be provided to KOMPSAT-2 project for agricultural application.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.155-157
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• 2024

Internet of Things (IoT) integrated with the Blockchain is the state of the art for keen cultivation and agriculture. Recently the interest in agribusiness information is enlarging owing to the fact of commercializing the smart farming technology. Agribusiness information are known to be untidy, and experts are worried about the legitimacy of information. The blockchain can be a potential answer for the expert's concern on the uncertainty of the agriculture data. This paper proposes an Agri-Banana plant system using Blockchain integrated with IoT. The system is designed by employing IoT sensors incorporated with Hyperledger fabric network, aims to provide farmers with secure storage for preserving the large amounts of IoT and agriculture data that cannot be tampered with. A banana smart contract is implemented between farmer peer and buyer peer of two different organizations under the Hyperledger fabric network setup aids in secure transaction of transferring banana from farmer to buyer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.6
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• pp.1391-1396
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• 2011

A way to increase productivity in agriculture that is labor-centered industry is to graft IT technology. Today, many technologies in ubiquitous computing are deployed in all areas of society such as traffic control, automotive manufacturing, construction, defence, healthcare and clinical services. These IT technologies is gaining more attention as a fusion technology among traditional industries. To successfully build ubiquitous agriculture environment, it needs optimized core technology development for agriculture that includes sensor node H/W, middleware platform, routing protocol and agriculture environment application services. To achieve accurate botany growth environment management, we propose a green growth environment management system using environmental factor monitoring sensor and biological information sensors in greenhouse. By using our proposed system, it is expected to realize fusion complex agriculture technology with low cost.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.521-530
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• 2018

This paper proposes "The Agriculture Decision-making System(ADS) based on Deep Learning for improving crop productivity" that collects weather information based on location supporting precision agriculture, predicts current crop condition by using the collected information and real time crop data, and notifies a farmer of the result. The system works as follows. The ICM(Information Collection Module) collects weather information based on location supporting precision agriculture. The DRCM(Deep learning based Risk Calculation Module) predicts whether the C, H, N and moisture content of soil are appropriate to grow specific crops according to current weather. The RNM(Risk Notification Module) notifies a farmer of the prediction result based on the DRCM. The proposed system improves the stability because it reduces the accuracy reduction rate as the amount of data increases and is apply the unsupervised learning to the analysis stage compared to the existing system. As a result, the simulation result shows that the ADS improved the success rate of data analysis by about 6%. And the ADS predicts the current crop growth condition accurately, prevents in advance the crop diseases in various environments, and provides the optimized condition for growing crops.

• Proceedings of the KSRS Conference
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• v.1
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• pp.432-435
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• 2006

Potential application topics of KOMPSAT-3 image in the field of precision agriculture are suggested. The topics can be categorized as fundamental and applied ones that have contents of static and dynamic characteristics respectively. As fundamental topics, precision information of agriculture that is related to farmland and its crop attributes, precision information of rural infrastructure that is related to rural village and its facilities, precision information of stream environment that is related to rural water resources and its facilities, and precision information of eco-environment that is especially related to riparian ecology and environmental status are included. As applied topics, precision rural water resources that has thematic contents of continuous and event-based runoff, spatial and temporal soil moisture and evapotranspiration, precision agricultural watershed environment that has the contents of spatial and temporal soil loss, sediment and pollutants transport, and precision temporal and spatial crop growth that has the contents of temporal crop texture, spectral reflectance, leaf area index, spatial crop protein information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.362-364
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• 2011

To build ubiquitous agriculture environment successfully, development of core technology for agriculture, such as sensor node H/W, sensor node middleware platform, routing protocol and agricultural environment application service is essential. With the application of u-IT technologies to traditional agriculture area, fusion complex technologies become a source to raise value-added agriculture product and its productivity. However, it is imperative to expand horticulture industry area and improve infrastructure for utility-based horticulture. This paper proposes an agriculture product growth environment management system that utilizes environmental factor monitoring sensors and biological information sensors in greenhouse to specifically manage botany growth environment management.