• Journal of Korean Society of Forest Science
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• v.88 no.2
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• pp.157-168
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• 1999

This paper analyzed vegetation and land use classification, slope and permanent preservation and legal reserves on the farm Jangada and Jamaica-Mato Grosso do Sul, Brazil, using satellite image for assisting the planning of planting Eucalyptus spp. This part of the State of Mato Grosso do Sul represents an important geopolitcal area, since it is located on the borders of Bolivia and Paraguay. Also exportation of goods can be achieved through hydrovias extending to Buenos Aires, Argentina-through the Paraguay River. Also there are road and railroad connection which link the soutreastern part of Brazil to the Andean countries. The vegetation map from sheet SF 21-Campo Grande of the RADAMBRASIL Project was used as the basis for the preliminary interpretation of coverage, and complemented by a visit of the field. After the initial interpretation of the image, definition of classes of use and land occupation were made, and files of spectral signatures were created. On the farms Jamaica and Jangada Open Arboreal Savanna and Grass Savanna are the predominant physiognomies occupying 68% of total area. In spite of the results being satisfactory at the present moment, the development of this project should be revised and adjusted based on the evaluations already made, including a greater detailing of environmental components, principally with respect to soil and topography.

• Journal of Korean Society on Water Environment
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• v.25 no.2
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• pp.193-204
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• 2009

The study was conducted investigation on land of D-dong in N city which is an urban area and D myeon of N city which is a suburban area, based on high resolution satellite image, to find out actual land usage. As for D-dong in N city, different rate between actual usage and official land information was 0.5~4.8% in terms of 5 major land types (paddy field, farm, ground, forest, and others). D myeon in N city posted 1.4~8.4%, which is higher than that of its counterpart. As for unit load, "land" which is large in terms of load presented a big difference between official information and actual usage. On the other hand, the levels of paddy, field, forest and others posted only small changes in load. In case of T-P, in particular, unit of each land type is lower than BOD and T-N, showing almost no changes in pollution loads.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.45-45
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• 2017

On-site monitoring of vegetable growth parameters, such as leaf length, leaf area, and fresh weight, in an agricultural field can provide useful information for farmers to establish farm management strategies suitable for optimum production of vegetables. Unmanned Aerial Vehicles (UAVs) are currently gaining a growing interest for agricultural applications. This study reports on validation testing of previously developed vegetable growth estimation models based on UAV-based RGB images for white radish and Chinese cabbage. Specific objective was to investigate the potential of the UAV-based RGB camera system for effectively quantifying temporal and spatial variability in the growth status of white radish and Chinese cabbage in a field. RGB images were acquired based on an automated flight mission with a multi-rotor UAV equipped with a low-cost RGB camera while automatically tracking on a predefined path. The acquired images were initially geo-located based on the log data of flight information saved into the UAV, and then mosaicked using a commerical image processing software. Otsu threshold-based crop coverage and DSM-based crop height were used as two predictor variables of the previously developed multiple linear regression models to estimate growth parameters of vegetables. The predictive capabilities of the UAV sensing system for estimating the growth parameters of the two vegetables were evaluated quantitatively by comparing to ground truth data. There were highly linear relationships between the actual and estimated leaf lengths, widths, and fresh weights, showing coefficients of determination up to 0.7. However, there were differences in slope between the ground truth and estimated values lower than 0.5, thereby requiring the use of a site-specific normalization method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1524-1530
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• 2018

In this paper, we designed a product that can prevent environmental pollution, waste of resources, and leakage of foreign currency by commercializing a green IT solution by merging a used smart phone with the IoT object communication technology for the first time in the world. For the experiment of the designed system, various performance and communication condition was experimented by installing it in the actual crop cultivation facility. As a result, when a problem occurs, the alarm sound and video notification are generated by the user's smart phone, and remote control of various installed devices and data analysis in real time are possible. In this study, it is thought that the terminal management board developed for the utilization of the used smart phone can be applied to various fields such as agriculture and environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1720-1728
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• 2022

The industrial 4.0 era has been opened with the development of artificial intelligence technology, and the realization of smart farms incorporating ICT technology is receiving great attention in the livestock industry. Among them, the quality management technology of livestock products and livestock operations incorporating computer vision-based artificial intelligence technology represent key technologies. However, the insufficient number of livestock image data for artificial intelligence model training and the severely unbalanced ratio of labels for recognizing a specific defective state are major obstacles to the related research and technology development. To overcome these problems, in this study, combining oversampling and adversarial case generation techniques is proposed as a method necessary to effectively utilizing small data labels for successful defect detection. In addition, experiments comparing performance and time cost of the applicable techniques were conducted. Through experiments, we confirm the validity of the proposed methods and draw utilization strategies from the study results.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.473-478
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• 2015

Recently, automatic video monitoring of individual pigs is emerging as an important issue in the management of group-housed pigs. Although a rich variety of studies have been reported on video monitoring techniques in intensive pig farming, it still requires further elaboration. In particular, when there exist adjoining pigs in a crowd pig room, it is necessary to have a way of separating adjoining pigs from the perspective of an image processing technique. In this paper, we propose an efficient image segmentation solution using both spatio-temporal information and region growing method for the identification of individual pigs in video surveillance systems. The experimental results with the videos obtained from a pig farm located in Sejong illustrated the efficiency of the proposed method.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.101-111
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• 2011

Due to recent development in wireless communication technologies and mobile information devices, the services on ubiquitous computing technology without time and place restriction have been spotlighted. Moreover, the interest of the Wireless Sensor Networks (WSNs) and context-awareness technologies have largely been escalating and their technologies utilization is active in the various applications such as healthcare, farm management and so on. However, the direct adaption of the existing context-awareness technique to the WSN technology has several drawbacks as follows. First, such systems waste precious energy of sensor nodes, due to unnecessary data transmissions. Secondly, since the existing work was designed to support only specific applications, it is required to implement a new context-awareness application for a specific purpose. Therefore, we, in this paper, propose a new real-time monitoring system based on context-awareness in WSNs. Our system not only enhances energy efficiency by reducing data transmissions by doing context-awareness on a sensor node, but also is scalable in terms of supporting new context-awareness functionalities through modularization.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.133-139
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• 2022

Recently, livestock farms in Korea are introducing data-based technologies to improve productivity, such as livestock environment and breeding management, safe livestock production, and animal welfare. In addition, the government has been conducting a smart livestock distribution project since 2017 through the modernization of ICT-based livestock facilities in order to improve the productivity of livestock products and improve the livestock environment as a policy. However, the current smart livestock house has limitations in connection, diversity, and integration between monitoring and control. Therefore, in order to intelligently systemize all processes of livestock with intelligent algorithms and remote control in order to link and integrate various monitoring and control, the Internet of Things, big data, artificial intelligence, cloud computing, and mobile It is necessary to develop a smart livestock system. In this study, domestic and foreign research trends related to smart livestock based on intelligent information technology were introduced and the limitations of domestic application of advanced technologies were analyzed. Finally, future intelligent information technology applicable to the livestock field was examined.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Journal of agricultural medicine and community health
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• v.32 no.3
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• pp.139-153
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• 2007

Injury in agriculture is a serious public health issue with a major impact on the lives of Korean farmers. It is one of the leading causes of death and is also a major cause of longand short-term disability. In 2001, the social cost of one accident in agricultural machinery was estimated as 97.7-97.8 million won that is 4 fold of farm household income in Korea. Effective prevention and control of injuries requires a system of surveillance that monitors the incidence of injuries, their causes, treatment and outcomes. This requires an integrated system of data collection, analysis and interpretation and communication. Creating effective injury surveillance system in Korea requires to establish a framework for a national agenda. Discussions regarding the development of the framework should address, but not be limited to issues related to Data Holdings and Linkages; Capacity and Skills; Communication; Interconnection; and Surveillance Products. Ideally, an injury surveillance system would meet the information requirements across all sectors, while allowing each to have the ongoing information it needs for its policy and programming needs. This study was carried out to develop a surveillance system of agricultural injuries in Korea. Study subjects were residents who lived in a typical agricultural area (Yangpyung area in Kyung-gi province). The main data sources were reports of village headmen, compared with data of 'National Emergency Management Agency', 'National Health Insurance Corporation', 'Insurance of National Agricultural Cooperative', and 'Emergency Medical Centers'. Each data were reviewed to validate the strengths and weaknesses.