• Agricultural and Biosystems Engineering
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• v.1 no.1
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• pp.59-62
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• 2000

After ten years of implementing the agricultural automation program in Taiwan, some positive effects and satisfactory results have been recognized by both the agricultural industry and local administrative bureaux. The automation of agriculture is a response to sophisticated demands for production and quality in countries with high labor costs. The development of sensor systems, control systems, precision agriculture systems, and engineering for plant culture systems will determine the degree of automation used for crop production in the 21st century. The engineering system will capitalize upon expertise from physiologists, pathologists, systems analysts, agronomists, horticulturists, computer programmers, economists, crop producers and managers in order to efficiently implement automated crop production.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.444-450
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• 2011

Environmental change, labor shortage, and international trade politics make agricultural automation ever more important. The automation demands the highest technology due to the nature of agriculture. In this paper, autonomous pesticide spray robot system has been developed for rose farming in the glass house. We developed drive platform, navigation/localization system, atomization spray system, autonomous, remote, and manual operation system, and monitoring system. The robot will be a great contribution to automation of hazardous labor-demanding chore of pesticide control in glass houses.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3782-3796
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• 2020

A three-dimensional (3D) reconstruction is an important research area in computer vision. The ability to detect and match features across multiple views of a scene is a critical initial step. The tracking matrix W obtained from a 3D reconstruction can be applied to structure from motion (SFM) algorithms for 3D modeling. We often fail to generate an acceptable number of features when processing face or medical images because such images typically contain large homogeneous regions with minimal variation in intensity. In this study, we seek to locate sufficient matching points not only in general images but also in face and medical images, where it is difficult to determine the feature points. The algorithm is implemented on an adaptive threshold value, a scale invariant feature transform (SIFT), affine SIFT, speeded up robust features (SURF), and affine SURF. By applying the algorithm to face and general images and studying the geometric errors, we can achieve quasi-dense matching points that satisfy well-functioning geometric constraints. We also demonstrate a 3D reconstruction with a respectable performance by applying a column space fitting algorithm, which is an SFM algorithm.

• 전자공학회논문지 IE
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• v.45 no.4
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• pp.19-26
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• 2008

The purpose of this paper is to build a system applicable to floriculture, hydroponics and vinyl house agriculture by a development of remote control equipments using programmable logic controllers (PLC). Remote factory automation and home automation systems have been developed and used due to the rapid progress in the fields of information and automation; however, the systems are so expensive that their applications have not been feasible in agriculture. So we have developed simple modules for PLC to replace the expensive conventional systems. The developed systems have potentials to be applied to automation systems in agricultural industry. Technologies for motor control, microprocessor, PLC programming and wireless interface are developed and implemented in the form of application modules of our systems, and our system is applicable to the remote form automation of floriculture and hydroponics.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.629-638
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• 2020

In this paper, an unmanned automation system for harvesting chili peppers through image recognition in the color space is proposed. We developed a cutting-edge technology in terms of convergence between information and communication technology (ICT) and agriculture. Agriculture requires a lot of manpower and entails hard work by the laborers. In this study, we developed an autonomous application that can obtain the head coordinates of a chili pepper using image recognition based on the OpenCV library. As an alternative solution to labor shortages in rural areas, a robot-based chili pepper harvester is proposed as a convergence technology between ICT and agriculture requiring hard labor. Although agriculture is currently a very important industry for human workers, in the future, we expect robots to have the capability of harvesting chili peppers autonomously.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.167-168
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• 2009

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.333-334
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• 2009

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.215-221
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• 2020

The paradigm of agriculture is also changing to address the problem of food shortages due to the increase of the world population, climate conditions that are increasingly subtropical, and labor shortages in rural areas due to aging population. With the development of Information Communication Technology (ICT), our daily lives are changing rapidly and heralds a major change in agricultural management. In a hyper-connected society, the introduction of high-tech into traditional Agriculture of the past is absolutely necessary. In the development process of Agriculture, the first generation produced by hand, the second generation applied mechanization, and the third generation introduced automation. The fourth generation is the current ICT operation and the fifth generation is artificial intelligence. This paper investigated Smart Farm that increases productivity through convergence of Agriculture and ICT, such as smart greenhouse, smart orchard and smart Livestock. With the development of sustainable food production methods in full swing to meet growing food demand, Smart Farming is emerging as the solution. In overseas cases, the Netherlands Smart Farm, the world's second-largest exporter of agricultural products, was surveyed. Agricultural automation using Smart Farms allows producers to harvest agricultural products in an accurate and predictable manner. It is time for the development of technology in Agriculture, which benchmarked cases of excellence abroad. Because ICT requires an understanding of Internet of Things (IoT), big data and artificial intelligence as predicting the future, we want to address the status of theory and actual Agriculture and propose future development measures. We hope that the study of the paper will solve the growing food problem of the world population and help the high productivity of Agriculture and smart strategies of sustainable Agriculture.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.142-159
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• 1996

Engineering of automated tools for the agro-food industries and the rural world activities have to pick up two challenges : to answer the immediate important problems related to the situation of these industries, and to imaging the tools that their professional will need next century. Creating or modifying automated tools in the next few will be made taking into account parameters either technical (environmental protection, health and safety), or social and economical (investment , employment). There will be a strong interaction with disciplines like ecology, medicine, ergonomy, psycho-sociology , etc. , The partners for such a research, tools manufactures and users, should have an early involvement in its content, in order to find rapidly the solution to the drastic problems they are meeting. On a longer term , during the next 20 years , there will be an important evolution of the rural space management and of the food processes. This will imply the emergence of new types of activities and know-how's , with lines of automated tools to be invented and developed , like : micro-system for organic localized tasks -mobile and adaptive equipments highly autonomous for natural space actions - device for perception , decision and control reproducing automatically the expert behaviors of human operators. Design of such automated tools need to overcome technological difficulties like the automation of the expert-decision process, or the management of complex design.

• Korean Journal of Agricultural Science
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• v.48 no.3
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• pp.617-627
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• 2021

In the field of on-road motor vehicles, the level for autonomous driving technology is defined according to J3016, proposed by Society of Automotive Engineers (SAE) International. However, in the field of agricultural machinery, different standards are applied by country and manufacturer, without a standardized classification for autonomous driving technology which makes it difficult to clearly define and accurately evaluate the autonomous driving technology, for agricultural machinery. In this study, a method to classify the autonomy levels for autonomous agricultural machinery (ALAAM) is proposed by modifying the SAE International J3016 to better characterize various agricultural operations such as tillage, spraying and harvesting. The ALAAM was classified into 6 levels from 0 (manual) to 5 (full automation) depending on the status of operator and autonomous system interventions for each item related to the automation of agricultural tasks such as straight-curve path driving, path-implement operation, operation-environmental awareness, error response, and task area planning. The core of the ALAAM classification is based on the relative roles between the operator and autonomous system for the automation of agricultural machines. The proposed ALAAM is expected to promote the establishment of a standard to classify the autonomous driving levels of self-propelled agricultural machinery.