• 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.

• Journal of Environmental Science International
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• v.28 no.5
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• pp.521-526
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• 2019

In this study, a solar light collector that collects and transmits solar light required for crop production in a closed plant production system was developed. The solar light collector consisted of a Fresnel lens for collecting solar light, and a tracking actuator for tracking solar light from sunrise to sunset to increase the light collection efficiency. The optical fiber that transmitted solar light was made of Glass Optical Fiber (GOF), and it had an excellent optical transmission rate. After collecting the solar light, the amount of light was measured at 5, 10, 15, 20, 25, and 30 cm distances from the GOF through the darkroom by using a light sensor logger connected to a quantum and pyranometer sensor. Compared with solar light, the light intensity of pyranometer sensor measured at 5 cm was 114% higher than solar light, and 61% at 10 cm. In addition, it was observed that it is possible to transmit the necessary amount of light for growing crops up to about 15 cm (as over 22%) through GOF. Therefore, adding diffusers to the solar light collector should be expected to replace artificial light in plant factories or plug seedlings nurseries for leafy vegetables. More studies on the solar light collection devices and the light transmission devices that have high light collection efficiency should be conducted.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.3
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• pp.1-14
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• 2024

Gaining an accurate 3D stream geometry has become feasible with Unmanned Aerial Vehicle (UAV), which is crucial for better understanding stream hydrodynamic processes. The objective of this study was to investigate series of filters to remove stream vegetation and propose the best method for generating Digital Terrain Models (DTMs) using UAV-based point clouds. A stream reach approximately 500 m of the Bokha stream in Icheon city was selected as the study area. Point clouds were obtained in August 1st, 2023, using Phantom 4 multispectral and Zenmuse L1 for Structure from Motion (SfM) and Light Detection And Ranging (LiDAR) respectively. Three vegetation filters, two morphological filters, and six composite filters which combined vegetation and morphological filters were applied in this study. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were used to assess each filters comparing with the two cross-sections measured by leveling survey. The vegetation filters performed better in SfM, especially for short vegetation areas, while the morphological filters demonstrated superior performance on LiDAR, particularly for taller vegetation areas. Overall, the composite filters combining advantages of two types of filters performed better than single filter application. The best method was the combination of Progressive TIN (PTIN) and Color Indicies of Vegetation Extraction (CIVE) for SfM, showing the smallest MAE of 0.169 m. The proposed method in this study can be utilized for constructing DTMs of stream and thus contribute to improving the accuracy of stream hydrodynamic simulations.

• Food Science and Preservation
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• v.30 no.3
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• pp.483-491
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• 2023

This study aimed to compare the bioactive compounds in Centella asiatica (C. asiatica) cultivated in a smart farm and a field and their effects on human keratinocyte cells. C. asiatica was collected in Jeju-do, Korea, and cultured in a smart farm and a field. The main bioactive compounds in the two differentially cultured C. asiatica were identified, and their activation in keratinocytes were assessed. Amplification and sequencing of the internal transcribed spacer (ITS) DNA in the nucleus and psbA-H DNA in the chloroplast were performed for species analysis. A comparison of DNA of plants reported in the NCBI GenBank was performed. The ITS DNA and psbA-H DNA sequences of C. asiatica cultivated in a smart farm and a field were consistent with No. MH768338.1 and No. JQ425422.1, respectively. Analysis of the triterpenes was performed using high performance liquid chromatography (HPLC) and as a result, C. asiatica cultured in a smart farm had more triterpenes than those cultured in a field. The effects of C. asiatica grown in a smart farm on cell proliferation and scratch recovery in HaCaT cells were greater than those grown in a field. These results suggest that C. asiatica cultivated in a smart farm can be effectively utilized as a health functional food.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.4
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• pp.161-173
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• 2020

As ICT convergence technology has spread and applied to various industrial fields and society in general, interest in rural entrepreneurship using smart farm as a means for solving many pending problems in agriculture is increasing. In this context, this study is to look at the influential factors in terms of perceived usefulness associated with the rural entrepreneurial intention using smart farm and suggest a proposal for spreading smart farms. The subjects were 296 general adults over 20 years old who were selected by simple random sampling method. The research method was exploratory factor analysis and multiple regression analysis using IBM SPSS 22.0. The perceived usefulness of smart farm, which are availability, reliability and economic efficiency were selected as independent variables to analyze the influential factors on rural entrepreneurial intention using smart farm and the moderating effect of personal innovation was observed. As a result, reliability and economic efficiency have a positive(+) influence on rural entrepreneurial intention using smart farm. And personal innovation moderates the relationship between the availability, reliability of smart farm and rural entrepreneurial intention using smart farm. The results of this study have significance in that we devised and empirically revealed factors affecting rural entrepreneurship intentions from the perspective of perceived usefulness of smart farms, away from studies of general entrepreneurship intention factors such as internal personal characteristics and external environmental factors. The implications of the study are expected to be utilized at the seeking direction of policy for potential entrepreneur using smart farm, the training and consulting in actual field of smart farm.

• Journal of Practical Agriculture & Fisheries Research
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• v.25 no.4
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• pp.67-77
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• 2024

This study analyzed the profitability and diagnosed business performance of fruit and vegetable (cherry tomatoes, tomatoes, strawberries, cucumbers) businesses targeting young farmers participating in the youth business incubation center of A Smart Farm Innovation Valley. The purpose of this is to provide basic data for decision-making by prospective young entrepreneurs. As a result of the analysis, Smart Farm Innovation Valley had the advantage of having a fixed rental fee. As a result, it was analyzed that various costs such as depreciation of large farm equipment, depreciation of farming facilities, repair and maintenance costs, land rent, floating capital service cost, fixed capital service cost, and land capital service cost are being reduced. However, excessive input of labor, water, electricity, other materials, and fertilizer costs was being made. Guidance to reduce these costs is expected to make a significant contribution to expanding the influx of young farmers.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.31-37
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• 2018

In this work, we propose an analytic framework for evaluating the quality of service and dimensioning the link capacity in the gateway router of a smart farm with a greenhouse eco-management system. Specifically, we focus on the gateway router of an IoT network that provides an access service for smart farms. We design the link capacity of a gateway router that is used for the remote management of the greenhouse eco-management system to accommodate both time-critical and delay-tolerant traffic in a greenhouse LAN. For this purpose, we first investigate the ecosystem for smart farm, and we define the specification and requirements of the greenhouse eco-management system. Second, we propose a system model for the link capacity of a gateway that is required to guarantee the delay performance of time-critical applications in the greenhouse LAN. Finally, the validity of the proposed system is demonstrated through a series of numerical experiments.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.851-858
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• 2018

In this paper, a temperature and humidity algorithm was proposed to enhance the economic efficiency and productivity of smart farm. The basic conditions of smart farms were analyzed, and the information exchange system between sensors and control objects in smart farms based on wireless communication was designed. Based on this, a temperature and humidity control algorithm was developed so that temperature, humidity and soil humidity within smart farm can be followed in predefined values for plant growth. To verify the validity of the proposed design methodology and control algorithm, a prototype of small scale smart farm based on 2.4GHz wireless communication were built and their validity was confirmed through repeated temperature and humidity test.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.681-682
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• 2018

There are many damages due to the unstable climate. Among them, agriculture will be the most affected by the climate. Agriculture has limited crops that can be grown along with climate and seasons. We will develop smart farms that integrate information technology(ICT) into agricultural technology and improve the productivity of existing agricultural technology. It uses Raspberry Pi and Arduino to control the hardware and software, and uses various sensors to recognize the environment necessary for crop cultivation and maintain optimal environment. In addition, it is possible to manipulate these Smart Farm as mobile or personal PC to implement a flexible Smart Farm.

• Journal of Korean Society of Rural Planning
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• v.26 no.3
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• pp.115-126
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• 2020

This study designed an extended technology acceptance model incorporating and combining TPB, TAM, UTAUT, and IDT, which are known to be useful in explaining technology acceptance intention, to analyze antecedents affecting smart farm acceptance intention from the perspective of policy handlers. In the model of this study, nine independent variables were set, including subjective norm, perceived behavioral control, attitude, perceived usefulness, performance expectation, effort expectation, social impact, promotion condition, and fitness. The effect of these variables on farm acceptance intention was analyzed. The study found that four factors, including perceived behavioral control, perceived usefulness, social impact, and fitness, had positive effects on the acceptance intention of smart farms. Of these, perceived usefulness had the highest impact. In conclusion, all the TPB, TAM, UTAUT, and IDT applied to the research hypothesis to explain the smart farm acceptance intention included on or more variables with significant effects. In other words, these theories were evaluated as useful to explain the acceptance intention of smart farms.