• 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 Korean Society for Quality Management
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• v.46 no.3
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• pp.707-716
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• 2018

Purpose: This study aims to analyze the management performance and production efficiency of strawberry farmers who introduced smart farming, one of the primary symbols of the fourth industrial revolution in the agricultural sector. Methods: We conducted an empirical survey of strawberry farms using smart farming and analyzed production efficiency using DEA method. Results: First, difficulties for strawberry farmers introducing smart farming included time and money spent on parts replacement and additional costs due to compatibility problems with existing facilities after the adoption. Second, strawberry farmers using smart farming increased their total income by producing higher yield and improving quality thanks to the competent growth management. Third, the analysis of production efficiencies before and after smart farming found improvement in technical efficiency, pure technical efficiency, and scale efficiency. But, the gaps in technical and scale efficiencies among the farms widened. Conclusion: Based on the results above, following policy suggestions are offered. First, an environment control technology suitable for strawberry farming needs to be developed. Second, the smart farming technology needs to be standardized by the government. Third, new smart farm models need to be developed to accommodate to the facilities and environment in Korea through collecting big data including high-quality data on the environment, growth, and yield. Fourth, continuing education needs to be provided to narrow the gap in smart farming technology among strawberry farmers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1534-1538
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• 2020

Smart farming education service focuses on the dissemination of farming information that is the farming knowledge, farming skill, and farmer's experiences and knowhow, etc. This farming information is supposed from current activities, farming product and from the experience of farmer on the field. If the information is not available, or if available and not in a form that is amenable to being brought to the end producer then the process stalls at this point. The core component of the automation process for smart farming education service is the creation of a data store which will be a repository for the information of the smart farming education. The farming sector will benefit immensely from the implementation of farming data in farming contents repository which will serve as the knowledge base for the smart farming education service.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.287-289
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• 2021

Smart farming education service based on network are important factors for farming sector. The lack of time and space has to lead to their limited appliance to farmers. Limited information support and low background knowledge in farming production is a lot of trial and error in farming production. Smart farming education as a service based on cloud provide the farming information that is the farming knowledge, farming skill, and farmer's experiences and knowhow, etc. And real-time information such as climate change, soil environment and market trends is very important. This paper proposes a framework for applying farming education service based on cloud. It consists of smart farming function and smart farming education function

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.617-618
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• 2015

IT convergence with agriculture is expected to bring more efficiency and quality improvement in pre-production stage, Production stage, post-production stage of agricultural products with the aid of information processing and autonomous control technologies of the IT area. This paper describes the actualized convergence service for agriculture, namely Smart Farming as a solution to cope various problems caused by severe conditions or the gap of viewpoints between the people engaged in farming and the IT engineers. In particular this defines service capabilities for Smart Farming, provides a reference model for Smart Farming, and identifies network capabilities required to produce an infrastructure which supports Smart Farming.

• Journal of Korean Society of Rural Planning
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• v.29 no.4
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• pp.127-135
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• 2023

This study examined the impact of changes in agricultural production methods on society, the economy, and the environment. While traditional open-field farming relied heavily on natural conditions, modern approaches, including greenhouse and smart farming, have emerged to mitigate the effects of climate and seasonal variations. Facility horticulture has been on the rise since the 1990s, and recently, there has been a growing interest in smart farms due to reasons such as climate change adaptation and food security. We compared open-field spinach and greenhouse spinach using agricultural income survey data, and we also compared greenhouse tomato cultivation with smart farming tomato cultivation, utilizing data from the smart farm survey reports. The economic results showed that greenhouse spinach increased yield by 25.8% but experienced a 29% decrease in income due to equipment depreciation. In the case of tomato production in smart farms, both yield and income increased by 36-39% and 34-46%, respectively. In terms of environmental impact, we also compared fertilizer and energy usage. It was found that greenhouse spinach used 29% less fertilizer but 14% more energy compared to open-field spinach. Smart farming for tomatoes saw a negligible decrease in electricity and fuel costs. Regarding the social impact, greenhouse spinach reduced labor hours by 31%, and the introduction of smart farming for tomatoes led to an average 11% reduction in labor hours. This reduction is expected to have a positive effect on sustainable farming. In conclusion, the transition from open-field to greenhouse cultivation and from greenhouse cultivation to smart farming appears to yield positive effects on the economy, environment, and society. Particularly, the reduction in labor hours is beneficial and could potentially contribute to an increase in rural populations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.607-612
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• 2017

IT convergence with agriculture and livestock farming are expected to bring more efficiency and quality improvement in producing, distributing, consuming of agricultural products with the aid of information processing and autonomous control technologies of the IT area. The standardization work for smart farming and livestock farming based on networks is just at the beginning stage. And also, it is capable of coping with environment and technical problems with the actualized IT convergence case for agriculture. Hence, more studies on each point are required to finish the works including amendments and enhancements. More interests are expected to attain the successful results that ultimately contribute to innovate in the lifestyle. In this paper, it is analyzed strategy item and consider the actualized IT convergence case for agriculture and livestock, namely Smart Farming and Smart livestock Farming as a solution to cope the presented problems. In addition, suggest to ICT standardization road map for future planning.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2703-2709
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• 2015

IT convergence with agriculture is expected to bring more efficiency and quality improvement in producing, distributing, consuming of agricultural products with the aid of information processing and autonomous control technologies of the IT area. Smart Farming based on network is a service which is capable of coping with environmental and technical problems with the actualized IT convergence case for agriculture. In this paper, it is required to consider the actualized IT convergence case for agriculture, namely Smart Farming as a solution to cope the presented problems. In addition, propose and suggest to standard model and standardization items requirement for the Smart Farming based on network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.600-602
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• 2015

This paper first introduces Smart Farming with various researches and developments, and describes its reference model. Then, the importance of planning at the pre-production stage which deeply affects to the whole process of the Smart Farming is explained. Lastly, the current and future trends of researches and developments on the planning of the Smart Farming are given.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.718-720
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• 2017

IT convergence with agriculture and livestock farming are expected to bring more efficiency and quality improvement in producing, distributing, consuming of agricultural products with the aid of information processing and autonomous control technologies of the IT area. In this paper, it is analyzed reference model and consider the actualized IT convergence case for agriculture and livestock, namely Smart Farming and Smart livestock Farming as a solution to cope the presented problems.