• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.310-313
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• 2012

Recently, Land reclamation created agricultural land which is farming. Agricultural land which is farming have accident with frequency it is damage to crop of from brine. So, desalinization is the first priority prerequisite task in using the in reclaimed farm land. Vibrant research and technical development is working for reclaimed of desaliaization. But, Current technology is impossible desalinization of reclaimed land. As fast almost of people don't worry about concentration of salt in using the land reclamation of agricultural land irrigation water and river mouth of fountainhead of efforting from freshwater lake also ebb and flow of the tide land reclamation of agricultural land influnce from an increase of salt concentration by weather conditions and a malfunction of sea dike sluice In this paper, current is increased salt concentration in real time graphs were implemented to utilize external servers in using the WCDMA module. Inaddition it have to operate alarm in increase of salt concentration. besides, this program have implemented realtime concentration of salt monitoring system which save date in realtime the user can check again.

• Advances in robotics research
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• v.2 no.3
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• pp.201-217
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• 2018

Agriculture production is a critical human intensive task, which takes place in all regions of the world. The process to grow and harvest crops is labor intensive in many countries due to the lack of automation and advanced technology. Much of the difficult, dangerous and dirty labor of crop production can be automated with intelligent and robotic platforms. We propose an intelligent, agent-oriented robotic team, which can enable the process of harvesting, gathering and collecting crops and fruits, of many types, from agricultural fields. This paper describes a novel robotic organization enabling humans, robots and agents to work together for automation of gathering and collection functions. The focus of the research is a model, called HARMS, which can enable Humans, software Agents, Robots, Machines and Sensors to work together indistinguishably. With this model, any capability-based human-like organization can be conceived and modeled, such as in manufacturing or agriculture. In this research, we model, design and implement a technology application of knowledge-based robot-to-robot and human-to-robot collaboration for an agricultural gathering and collection function. The gathering and collection functions were chosen as they are some of the most labor intensive and least automated processes in the process acquisition of agricultural products. The use of robotic organizations can reduce human labor and increase efficiency allowing people to focus on higher level tasks and minimizing the backbreaking tasks of agricultural production in the future. In this work, the HARMS model was applied to three different robotic instances and an integrated test was completed with satisfactory results that show the basic promise of this research.

• Journal of Biosystems Engineering
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• v.31 no.1 s.114
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• pp.52-58
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• 2006

Various robots were developed for harvesting fruits and vegetables. However, each robot was designed for a specific task such as harvesting apples or vegetables. This has been a big hurdle in application of robots to agriculture. A new type of hybrid manipulator with both parallel and serial joints was developed and designed to apply to various kinds of field operations. The hybrid manipulator had 2 extra degree of freedom in serial joints which made it flexible in switching one to the other type of hybrid manipulator, for example, PUMA to SCARA. And it was designed to harvest heavy fruits such as musky melons or water melons even behind leaves or branches of tree. This hybrid manipulator showed less than $\pm1mm$ position error. It was concluded that the hybrid manipulator was an effective and feasible tool to perform various works and to increase working performance.

• Journal of Biosystems Engineering
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• v.33 no.1
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• pp.14-20
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• 2008

An agricultural unmanned helicopter was suggested for an alternative to current pesticide application methods to solve such problems as high cost, low efficiency, shirking task and unsafe work. To pursuit this trend, researches on the development of unmanned helicopters have been accelerated in Korea as well. In this research, a guide type centrifugal clutch that plays an important role in the unmanned helicopter was studied. Theoretical analyses and experimental tests were conducted for designing an optimal clutches. Main design factors of the guide type centrifugal clutch were found to be spring constant, free length of spring, mass of friction sector, contact area, allowable pressure, number of friction sector, friction coefficient, radius of drum, and clutch arrangement. And these design factors could be the functions of engaging engine speed and desired power transfer capacity. The result of the single clutch test showed the power transfer capacity of 14.1 PS at 5,800 rpm and the result of the dual clutch test showed that the capacity of 17.7 PS at 5,600 rpm. These experimental results agreed well the theoretical simulations.

• Journal of Construction Engineering and Project Management
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• v.7 no.2
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• pp.34-44
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• 2017

The use of Unmanned Aircraft Systems (UASs) in the construction and agriculture industries continues to gain in popularity and use. Firms within these industries have begun to utilize UASs to perform many of the traditional processes and procedures, which can result in a reduction in total work force and costs needed for a task. However, as with any technology, there is a learning curve and UASs do change the way certain activities are completed. Due to this, there exist firms and individuals that have not or are not willing to invest in UASs yet. The objective of this study is to explore the applications of UASs in construction and agricultural industries to discuss the benefits, challenges, and reasons of investing in UASs. This paper conducted an in-depth literature review of current topics on UASs in construction and agriculture. Additionally, six expert interviews were conducted with individuals from construction and agricultural industries in the southeastern United States. Ultimately, this study successfully found several benefits and challenges to using UASs and discussed the reasons that some firms invest in UASs while other still do not.

• The Journal of Fisheries Business Administration
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• v.26 no.2
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• pp.133-146
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• 1995

WTO system has just begun and the development for fishing industry is being carried out. The task of National Federation of Fisheries Cooperatives(NFFC ) is not only to support producers' competitive edge, but also to realize the efficiency embodied in the businesses of NFFC itself. Then it can continue to compete other firms and offer the comprehensive services only when it achieves its efficiency. The efficiency of NFFC is the economies of scale and scope. NFFC should achieve its scale and scope economies to be efficient. NFFC needs to expand its size in fish distribution and banking business to have scale economies. Also, the communication and coordination systems among member-supporting, fish distribution, and banking business need to be strengthened to get its scope economies. It is interesting theoretically and in policy making to test the hypotheses that cooperatives are capable of offering the comprehensive services such as distribution, credit, and insurance to the members. It is meaningful to their development for agricultural and small businesses cooperatives as well as fisheries cooperatives to survive the fierce competition under WTO system. National Federation of Agricultural Cooperatives(NFAC) is much greater in business size than NFFC. The estimation and test in the multiproduct cost function of NFAC will show interesting results.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.279-286
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• 2000

The objective of this research is to detect the papaya fruits on tree in an orchard. The detection of papaya on natural background is difficult because colors of fruits and background such as leaves are similarly green. We cannot separate it from leaves by color information. Therefore, this research will use shape information instead. First, we detect an interested object by detecting its boundary using edge detection technique. However, the edge detection will detect every objects boundary in the image. Therefore, shape description technique will be used to describe which one is the interested object boundary. The good shape description should be invariant in scaling, rotating, and translating. The successful concept is to use Fourier series, which is called "Fourier Descriptors". Elliptic Fourier Descriptors can completely represent any shape, which is selected to describe the shape of papaya. From the edge detection image, it takes a long time to match every boundary directly. The pre-processing task will reduce non-papaya edge to speed up matching time. The deformable template is used to optimize the matching. Then, clustering the similar shapes by the distance between each centroid, papaya can be completely detected from the background.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.3
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• pp.75-84
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• 2013

The seepage quantity analysis of reservoir embankment is very important for assessment of embankment safety. However, the conventional analysis does not consider uncertainty of soil properties. Permeability is known that the coefficient of variation is larger than other soil properties and seepage quantity is highly dependent on the permeability of embankment. Therefore, probabilistic analysis should be carried out for seepage analysis. To designers, however, the probabilistic analysis is not an easy task. In this paper, the method that can be performed probabilistic analysis easily and efficiently through the numerical analysis based commercial program is proposed. Stochastic response surface method is used for approximate the limit state function and when estimating the coefficients, the moving least squares method is applied in order to reduce local error. The probabilistic analysis is performed by LHC-MCS through the response surface. This method was applied to two type (homogeneous, core zone) earth dams and permeability of embankment body and core are considered as random variables. As a result, seepage quantity was predicted effectively by response surface and probabilistic analysis could be successfully implemented.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.3
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• pp.141-148
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• 2012

Food policy is considered as the most basic and central issue for all countries, while making efforts to keep each country's food sovereignty and enhance food self-sufficiency. In the case of Korea where the staple food is rice, the rice yield prediction is regarded as a very important task to cope with unstable food supply at a national level. In this study, Korean paddy Rice yield Prediction Model (KRPM) developed to predict the paddy rice yield using meteorological element and MODIS NDVI. A multiple linear regression analysis was carried out by using the NDVI extracted from satellite image. Six meteorological elements include average temperature; maximum temperature; minimum temperature; rainfall; accumulated rainfall and duration of sunshine. Concerning the evaluation for the applicability of the KRPM, the accuracy assessment was carried out through correlation analysis between predicted and provided data by the National Statistical Office of paddy rice yield in 2011. The 2011 predicted yield of paddy rice by KRPM was 505 kg/10a at whole country level and 487 kg/10a by agroclimatic zones using stepwise regression while the predicted value by KOrea Statistical Information Service was 532 kg/10a. The characteristics of changes in paddy rice yield according to NDVI and other meteorological elements were well reflected by the KRPM.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.51-62
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• 2021

Plant disease is one of the issues that can create losses in the production and economy of the agricultural sector. Early detection of this disease for finding solutions and treatments is still a challenge in the sustainable agriculture field. Currently, image processing techniques and machine learning methods have been applied to detect plant diseases successfully. However, the effectiveness of these methods still needs to be improved, especially in multiclass plant diseases classification. In this paper, a convolutional neural network with a batch normalization-based deep learning approach for classifying plant diseases is used to develop an automatic diagnostic assistance system for leaf diseases. The significance of using deep learning technology is to make the system be end-to-end, automatic, accurate, less expensive, and more convenient to detect plant diseases from their leaves. For evaluating the proposed model, an experiment is conducted on a public dataset contains 20654 images with 15 plant diseases. The experimental validation results on 20% of the dataset showed that the model is able to classify the 15 plant diseases labels with 96.4% testing accuracy and 0.168 testing loss. These results confirmed the applicability and effectiveness of the proposed model for the plant disease detection task.