• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.299-305
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• 2021

Dissolved oxygen, pH, and temperature are the most important factors for fish farming because they affect fish growth and mass mortality of the fish. Therefore, fish farm workers must always check all pools on the farm, but this is very difficult in reality. That's why we developed a control system for smart fish farms. This system includes a gateway, sensor gatherers, and a PC program using LabVIEW. One sensor gatherer can cover up to four pools. The sensor gatherers are connected to the gateway in the form of a bus. For the gateway, the ATmega2560 is used as the main processor for communication and the STM32F429 is used as a sub-processor for displaying LCD. For the sensor gatherer, ATmega2560 is used as the main processor for communication. MQTT (Message Queuing Telemetry Transport), RS-485, and Zigbee are used as the communication protocols in the control system. The users can control the temperature and the dissolved oxygen using the PC program. The commands are transferred from the PC program to the gateway through the MQTT protocol. When the gateway gets the commands, it transfers the commands to the appropriate sensor gatherer through RS-485 and Zigbee.

• Journal of Digital Convergence
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• v.18 no.3
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• pp.171-177
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• 2020

Under the influence of the Fourth Industrial Revolution, there are many tries to promote productivity enhancement and competitiveness by adapting smart farm technology that converges ICT technologies in agriculture. This smart farming technology is emerging as a new paradigm for future growth in agriculture. The development of real-time cultivation environment monitoring and automatic control system is needed to implement smart farm. Furthermore, the development of intelligent system that manages cultivation environment using monitoring data of the growth of crops is required. In this paper, a fast and efficient development method for implementing a cloud-based smart farm management system using a highly compatible and scalable web platform is proposed. It was verified that the proposed method using the web platform is effective and stable system implementation through the operation of the actual implementation system.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.378-388
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• 2016

International societies are currently working together to achieve the Climate-Smart Agriculture (CSA) initiative which aims the triple wins: (1) sustainably increasing agricultural productivity and incomes; (2) adapting and building resilience to climate change; and (3) mitigating greenhouse gases emissions. In terms of its scope and context, CSA follows the '3Nong (三農)' vision cast about 200 years ago by Dasan Jeong Yak-Yong who emphasized the triad of governance, management and monitoring towards comfortable, profitable and noble agriculture. Yet, the CSA provides the practical aims that facilitate the development of holistic indicators for quantitative evaluation and monitoring, on which decision-making support system is based. In this study, we introduce an agent-based model, i.e. Mathematical Programming Multi-Agent Systems (MP-MAS), as a tool for supporting the decision-making toward CSA. We have established the initial version of MP-MAS adapted for domestic use and present the preliminary results from an application to the rice farming case in Haenam, Korea. MP-MAS can support both farmers and policy-makers to consider diverse management options from multiple perspectives. When the modules for system resilience and carbon footprint are added, MP-MAS will serve as a robust tool that fulfills not only CSA but also Dasan's '3Nong' vision of sustainable agricultural-societal systems.

• Journal of Soil and Groundwater Environment
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• v.28 no.5
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• pp.51-58
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• 2023

In this study, an empirical experiment was conducted to assess the feasibility of replacing groundwater with rainwater in melon cultivation using a smart rainwater harvesting system. The rainwater harvesting efficiency was calculated under three different melon cultivation scenarios. After cultivation, the quality of the fruits grown with rainwater and groundwater was compared by examining the weight, degree of sweetness, and flesh hardness of the products. The results revealed that the water quality of the smart rainwater harvesting device was suitable for melon cultivation to provide better hardness and chloride levels than groundwater. It was also estimated that about 40% of the total water demand for full growth of the melon could be supplied by rainwater. The fruit weight and sweetness were equivalent or slightly better for the melons cultivated with rainwater than those cultivated with groundwater. In particular, the flesh hardness was significantly improved by rainwater cultivation. These results collectively suggest that rainwater can be used as a substitute for groundwater to preserve groundwater resources without compromizing the produced fruit quality.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.112-122
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• 2022

Food security and its sovereignty have become among the most important key issues due to changes in the international situation. Regarding these issues, many countries now give attention to smart agriculture, which would increase production efficiency through a data-based system. The Korean government also has attempted to promote smart agriculture by 1) implementing the agri-food ICT (information and communications technology) policy, and 2) increasing the R&D budget by more than double in recent years. However, its endeavors only centered on large-scale farms which a number of domestic farmers rarely utilized in their farming. To promote smart agriculture more effectively, we diagnosed the government R&D trends of smart agriculture based on NTIS (National Science and Technology Information Service) data. We identified the research trends for each R&D period by analyzing three pieces of information: the regional information, research actor, and topic. Based on these findings, we could suggest systematic R&D directions and implications.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.79-79
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• 2023

With the development of digital technology, the size of the smart agriculture market at home and abroad is rapidly expanding. It is necessary to establish a foundation for sustainable precision agriculture in order to respond to the aging of rural areas and labor shortages. This study was conducted to establish an automated digital agricultural test bed for soybean production management using data suitable for agricultural environmental conditions in Korea and to demonstrate the field of leading complexes. In order to manage water smartly, we installed a subsurface drip irrigation system in the upland field and an underground water level control system in the paddy field. Based on data collected from sensors, water management was controlled by utilizing an integrated control system. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. The main growth characteristics and yield, such as stem length, number of branches, and number of nodes of the main stem, were investigated during the main growth period. During the operation of the test bed, drought appeared during the early vegetative growth period and maturity period, but in the open field smart agriculture test bed, water was automatically supplied, reducing labor by 53% and increasing yield by 2%. A test bed was installed for each field digital farming element technology, and it is planned to verify it once more this year. In the future, we plan to expand the field digital farming technology developed for leading farmers to the field.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.743-748
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• 2021

Amid the global population growth and climate change, high-tech smart farm technology that combines agriculture and ICT is actively being researched in Korea to solve sustainable crises such as declining population of agricultural and livestock industries. Existing smart farms are growing mainly on crops with low price competitiveness. Food consumption structures are becoming more sophisticated and diverse, and as agricultural consumption patterns change, the smart farm system also needs to be optimized for growing high-value special crops. To this end, an integrated ICT management system was designed and implemented by establishing a containerized smart farm environment specialized in growing sprout ginseng. Through this, it is possible to implement high-tech agricultural production and lead new future convergence industries through the convergence of ICT, agriculture, and the latest technologies and farming.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.58-58
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• 2022

With the development of advanced technology, automation of agricultural work is spreading. In association with the 4th industrial revolution-based technology, research on field smart farm technology is being actively conducted. A state-of-the-art unmanned automated agricultural production demonstration complex was established in Naju-si, Jeollanam-do. For the operation of the demonstration area platform, it is necessary to build a sophisticated, advanced, and intelligent field smart farming model. For the operation of the unmanned automated agricultural production demonstration area platform, we are building data on the growth of soybean for smart cultivated crops and conducting research to determine the optimal time for agricultural work. In order to operate an unmanned automation platform, data is collected to discover digital factors for water management immediately after planting, water management during the growing season, and determination of harvest time. A subsurface drip irrigation system was established for smart water management. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. Vegetation indices were collected using drones to find key factors in soybean production prediction. In addition, major growth characteristics such as stem length, number of branches, number of nodes on the main stem, leaf area index, and dry weight were investigated. By discovering digital factors for effective decision-making through data construction, it is expected to greatly enhance the efficiency of the operation of the unmanned automated agricultural production demonstration area.

• Applied Chemistry for Engineering
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• v.33 no.4
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• pp.335-342
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• 2022

In the agricultural sector where the fossil fuels are primary energy resources, the current global energy crisis together with the dissemination of smart farming has led to the new phase of energy pattern in which the electricity demand is growing faster particularly. Therefore, the fuel cell combined heat and power system, coupling the environmentally friendly fuel cell to biomass treatment and feeding, can be regarded as the most effective energy system in agriculture. In this mini-review, we discuss the R&D trend of the fuel cell combined heat and power system aimed at utilizing agricultural by-products as fuels and highlight the issues in terms of the process configuration and interconnection of individual processes.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.71-78
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• 2022

Recently, the number of people wishing to return to farming is increasing, However, the lack of farming experience and management information of returnees is one of the main reasons for increasing the probability of agricultural failure. This study proposes an interface to support early facility cultivation management decision-making for returnees who want facility cultivation. The proposed interface is designed with UML(Unified Modeling Language) and provides key decision-making information such as land/crop suitability, land/facility costs, and management costs according to input data such as cultivation areas, selected crops, and cultivation types selected by the user. Through the proposed interface, facility cultivators can effectively and quickly acquire initial decision-making information for facility cultivation in the desired target area.