• Convergence Security Journal
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• v.22 no.5
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• pp.69-80
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• 2022

Now that climate change and food resource security are becoming issues around the world, smart farms are emerging as an alternative to solve them. In addition, changes in the production environment in the primary industry are a major concern for people engaged in all primary industries (agriculture, livestock, fishery), and the resulting food shortage problem is an important problem that we all need to solve. In order to solve this problem, in the primary industry, efforts are made to solve the food shortage problem through productivity improvement by introducing smart farms using the 4th industrial revolution such as ICT and BT and IoT big data and artificial intelligence technologies. This is done through the public and private sectors.This paper intends to consider the minimum requirements for the smart farm data collection system for the development and utilization of smart farms, the establishment of a sustainable agricultural management system, the sequential system construction method, and the purposeful, efficient and usable data collection system. In particular, we analyze and improve the problems of the data collection system for building a Korean smart farm standard model, which is facing limitations, based on in-depth investigations in the field of livestock and livestock (pig farming) and analysis of various cases, to establish an efficient and usable big data collection system. The goal is to propose a method for collecting big data.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.719-729
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• 2017

Recently, the field of agriculture has been gaining a new leap with the integration of ICT technology in agriculture. In particular, smart farms, which incorporate the Internet of Things (IoT) technology in agriculture, are in the spotlight. Smart farm technology collects and analyzes information such as temperature and humidity of the environment where crops are cultivated in real time using sensors to automatically control the devices necessary for harvesting crops in the control device, Environment. Although smart farm technology is paying attention as if it can solve everything, most of the research focuses only on increasing crop yields. This paper focuses on the development of a system architecture that can harvest high quality crops at the optimum stage rather than increase crop yields. In this paper, we have developed an architecture using apple trees as a sample and used the color information and weight information to predict the harvest time of apple trees. The simple board that collects color information and weight information and transmits it to the server side uses Arduino and adopts model-driven development (MDD) as development methodology. We have developed an architecture to provide services to PC users in the form of Web and to provide Smart Phone users with services in the form of hybrid apps. We also developed an architecture that uses beacon technology to provide orchestration information to users in real time.

• Korean Journal of Organic Agriculture
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• v.31 no.3
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• pp.229-247
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• 2023

This study investigates the facility use status of smart farming farmers to improve facility use rate of farmers. To this end, a survey was conducted on smart farming farmers in Jeonnam province, and the main survey contents are as follows: facility use rate, the reasons for low facility use, the perception of the introduction and use of smart farming etc. As a result of the survey, many farmers have introduced smart farming facilities even though they do not have enough use capacity. Thus it is necessary to improve the use capacity of farmers. Second, the average facility use rate of farmers was 65.1%, and 37.5% of respondents did not use even 50% of smart farming facilities. To improve the use rate, education on how to use facilities and continuous consulting support for farmers are needed. And the largest number of farmers perceived the risk like crop damage or facility failure due to poor use of facilities. This means that risk management due to the smart farming facilities is important. Third, farmers answered that rapid and continuous repair service were the most important when using facilities. Thus it is important to foster rear industries such as maintenance companies to stably operate smart farming facilities.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.183-189
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• 2021

In this study, we developed a "Korean-style button mushroom cultivation Compost post-fermentation system." The purpose is to increase farm income by reducing the labor force of button mushrooms farmers and shortening the production cycle. The "Korean-style button mushroom cultivation Compost post-fermentation system" was designed to reflect the reality of domestic button mushroom farmers. By reducing the temperature difference of the fermentation Compost in the fermentation system, the company produces a button mushroom Compost that ensures uniform quality. As a result of the performance experiment, the working time of the Compost post-fermentation system was shortened by 40 hours. The number of aerobic bacteria and actinomyces that help the button mushrooms Compost increased. Filamentous bacteria that deteriorate the quality of mushrooms have been sterilized.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.376-378
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• 2021

According to the 2020 Global Climate Report released by the World Meteorological Organization, the average temperature of the Earth in 2019 was measured 1.1℃ higher on average than the temperature measured between 1850 and 1900 before industrialization. The change in average temperature affects the distribution of plants, and according to the vulnerability analysis paper, it can be seen that there is a change in the distribution area of plants when the average temperature rises. In this paper, to cope with these environmental changes, we propose a method of fabricating intermittent flow hydroponic smart farms using Arduino and sensors and controlling them through PCs and applications. The manufactured hydroponic smart farm identifies the farm's temperature and humidity, positive pH concentration, illumination, and water quality to check the amount of pumping, supplement LED control, sensor condition, overall management and cultivation of the farm, and grows in an appropriate environment.

• Journal of Sensor Science and Technology
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• v.33 no.4
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• pp.230-236
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• 2024

This study aimed to analyze the environmental factors affecting tomato growth by examining the correlation between weather and growth environment sensor data from P Smart Farm located in Gwangseok-myeon, Nonsan-si, Chungcheongnam-do. Key environmental variables such as the temperature, humidity, sunlight hours, solar radiation, and daily light integral (DLI) significantly affect tomato growth. The optimal temperature and DLI conditions play crucial roles in enhancing tomato growth and the photosynthetic efficiency. In this study, we developed a model to correct and predict the time-series variations in internal environmental sensor data using external weather sensor data. A linear regression analysis model was employed to estimate the external temperature variations and internal DLI values of P Smart Farm. Then, regression equations were derived based on these data. The analysis verified that the estimated variations in external temperature and internal DLI are explained effectively by the regression models. In this research, we analyzed and monitored smart-farm growth environment data based on weather sensor data. Thereby, we obtained an optimized model for the temperature and light conditions crucial for tomato growth. Additionally, the study emphasizes the importance of sensor-based data analysis in dynamically adjusting the tomato growth environment according to the variations in weather and growth conditions. The observations of this study indicate that analytical solutions using public weather data can provide data-driven operational experiences and productivity improvements for small- and medium-sized facility farms that cannot afford expensive sensors.

• Transactions of Materials Processing
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• v.32 no.3
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• pp.153-159
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• 2023

This paper presents the optimal design of a heating system using radiant heating elements for application in smart farms. Smart farming, an advanced agricultural technology, is based on artificial intelligence and the internet of things and promotes crop production. Temperature and humidity regulation is critical in smart farms, and thus, a heating system is essential. Radiant heating elements are devices that generate heat using electrical energy. Among other applications, radiant heating elements are used for environmental control and heating in smart farm greenhouses. The performance of these elements is directly related to their electrical energy consumption. Therefore, achieving a balance between efficient electrical energy consumption and maximum heating performance in smart farms is crucial for the optimal design of radiant heating elements. In this study, the size, electrical energy supply, heat generation efficiency, and heating performance of radiant heating elements used in these heating systems were investigated. The effects of the size and electrical energy supply of radiant heating elements on the heating performance were experimentally analyzed. As the radiant heating element size increased, the heat generation efficiency improved, but the electrical energy consumption also increased. In addition, increasing the electrical energy supply improved both the heat generation efficiency and heating performance of the radiant heating elements. Based on these results, a method for determining the optimal size and electrical energy supply of radiant heating elements was proposed, and it reduced the electrical energy consumption while maintaining an appropriate heating performance in smart farms. These research findings are expected to contribute to energy conservation and performance improvement in smart farming.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.17-27
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• 2012

Most of the current cultivation log is recorded by growers manually or whose environment information is input based on the grower's own judgement. It is not easy for growers to record the image of disease and insect pests in the cultivation log. In this regards, u-Farm cultivation log management system based on Web 2.0 and smart phone is introduced in this paper, that is used for the effective cultivation management and grower's convenience. In the system, the value of environment information is transmitted to servers via sensors. It designs and implements Web 2.0 Flex so as to make the cultivation log more reliable and provide users with active, convenient GUI in case the log is recorded by desktop. In this process, detailed modules are designed by object-oriented UML considering the reusability and maintenance of the system. Moreover, the system introduced in this paper is proved to be more excellent by the qualitative assessment compared with the other researches.

• 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 Information Processing Systems
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• v.17 no.6
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• pp.1179-1190
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• 2021

A data acquisition and monitoring system was developed for an automated system of a smart fish farm. The fish farm is located in Jang Hang, South Korea, and was designed as circulation filtration system. Information of every aquaculture pool was automatically measured by pH sensors, dissolved oxygen sensors, and water temperature sensors and the data were stored in the database in a remoted server. Modbus protocol was used for gathering the data which were further used to optimize the pool water quality to predict the rate of growth and death of fish, and to deliver food automatically as planned by the fish farmer. By using JSON protocol, the collected data was delivered to the user's PC and mobile phone for analysis and easy monitoring. The developed monitoring system allowed the fish farmers to improve fish productivity and maximize profits.