• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.719-724
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• 2021

In this paper, we studied properties of smart farms that can automatically control not only the temperature and humidity but also the illumination to improve plant productivity. The smart farm was designed to allow the controllers to operate through Arduino by receiving input values from each sensor. In addition, to maximize the convenience of smart farm, the Bluetooth communication module is used to control the smart phone. The study confirmed that the automation function of smart farms can create an environment suitable for plants to grow.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.405-407
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• 2017

The environmental change is affecting the farm products like tomato, and pepper, etc. This affects to lead smart farming yield. What is more, this inconstant conditions cause the farms to be infected by variety diseases. Therefore ICT technology is needed to detect and prevent the crops from being effected by diseases. This article suggests the procedure to help producer for identifying farms disease based on the detected image. This detects the kind of diseases with comparing the trained image data before and after disease emergence. First step monitors an image of farms and resize it. Its features are extracted on parameters such as color, and morphology, etc. The next steps are used for classification to classify the image as infected or non-infected. on the bassis of detection algorithm.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.65-75
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• 2017

Agricultural sector in Korea faces the threat of aging farmers and many other difficulties. Because agriculture is a very less-competitive industry in Korea and many solutions to improve the competitiveness of Korean agriculture should be studied. The advent of Internet of things(IoT) technology makes possible many new industries and business models in the current society. The adoption of this new technology in agriculture can bring about innovations in agricultural production and distribution as $6^{th}$ industry. This paper summarizes the opportunities in IoT and smart farm. The major benefits and obstacles in introducing smart farms are reviewed and the cases of two successful smart farms in Korea are analyzed. Through these case studies, we can recognize the current status and future strategies in Korean smart farms.

• Smart Media Journal
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• v.11 no.4
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• pp.19-29
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• 2022

Recently, with the development of IoT technology, the number of farms using smart farms is increasing. Smart farms monitor the environment and optimise internal environment automatically to improve crop yield and quality. For optimized crop cultivation, researches on predict crop productivity are actively studied, by using collected agricultural digital data. However, most of the existing studies are based on statistical models based on existing statistical data, and thus there is a problem with low prediction accuracy. In this paper, we use various predition models for predicting the production and sales profits, and compare the performance results through models by using the agricultural digital data collected in the facility horticultural smart farm. The models that compared the performance are multiple linear regression, support vector machine, artificial neural network, recurrent neural network, LSTM, and ConvLSTM. As a result of performance comparison, ConvLSTM showed the best performance in R2 value and RMSE value.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.15-20
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• 2022

With the arrival of the fourth industrial era, demand for agriculture is increasing day by day, and smart farm technology, in which computers manage agriculture in line with the current situation, is developing. However, agricultural workers who use it find it difficult to set up and use a management system for smart farms. This paper aims to establish a Lab-View smart farm management system to facilitate the use of a control program for ICT technology farms (hereinafter referred to as smart farms), one of the promising projects of the next industrial revolution. Based on Lab-View, users simply set the type of crops they want to grow, set appropriate temperature/humidity data for each set crop, and collect data in real time through sensors and store it in DB. This functionality maximizes convenience and usability in terms of users.

• Journal of Mushroom
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• v.15 no.4
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• pp.206-209
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• 2017

In this study, the morphology and antioxidant content of shiitake mushrooms (Lentinula edodes) cultivated in smart farms and general farms have been compared. With regard to morphology, mushrooms produced in the smart farm system exhibited a slightly thicker and wider pileus and thicker and longer stipe than those in the general farm system. The stipe in the mushrooms from moderate-sized farms was harder, because the low relative humidity of cultivation rooms could induce mushroom tissue to harden. With regard to the antioxidant content, the free radical scavenging activity was evaluated by the DPPH assay. Among the various treatments, hot water extracts of freeze-dried shiitake produced from smart farms exhibited the highest DPPH value of 37.8%. In contrast, the lowest activity of 12.2% was observed in a 70% fermented alcohol extract of shiitake that was dried by hot air. The polyphenol content was higher in hot water extracts than in 70% fermented alcohol extracts. Additionally, the polyphenol content was higher in the freeze-dried samples than in hot-air dried ones. The smart-farm system was preferred over the general cropping system for cultivating shiitake mushrooms, because the antioxidant activity and polyphenol content of mushrooms from the smart-farm system was better; the functionality of this system was more improved than that of the general cropping system, and it enables mushrooms to be cultivated more efficiently. The antioxidant content is represented as the $mean{\pm}SD$ of three replicates. Different letters indicate significant differences among samples, i.e., p<0.05.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.559-564
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• 2021

With the development of ICT, research on smart farms is steadily progressing in the agricultural field for the modernization of cultivation facilities. However, most of the current smart farms are not specific crops, but general-purpose systems that can be used in various fields. In this paper, an environmental control device and an integrated control system capable of creating a aseptic growing environment required for mushroom cultivation were proposed, and the system was designed, manufactured, and programmed. Through this, it is possible to build a smart farm optimized for crops that is needed to maintain a precise growing environment.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1379-1386
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• 2018

Conventional underwater cameras used in fish farms can only shoot limited areas and are vulnerable to underwater contamination. There is also a problem with contaminated farms as surplus residues are deposited as a result of feed supply to farms' nets. This paper proposes underwater drones for underwater monitoring of fish farms and cleaning nets. If underwater drones are used for management of fish farms, underwater imaging, monitoring and cleaning of fish farms' nets can be possible. By using this technology, data can be collected by detecting changes in the environment of a fish farm and responding to changes that occur within a fish farm based on the data. In addition, the establishment of an integrated control system will enable to build efficient and stable smart farms.

• 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.