• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.27-35
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• 2007

The majority of farm managers growing the garden products in greenhouse concern massively about the diagnosis and prevention of the breeding and extermination for pests. especially, the managing problem for pests turns up as main issue. In the paper, we first build a wireless sensor network with soil and environment sensors such as illumination, temperature and humidity. And then we design and implement multimedia pest predication and management system which is able to predict and manage various pest of garden products in greenhouse. The proposed system can support the database with information about the pests by building up wireless sensor network in greenhouse compared with existing high-priced PLC device as well as collect various environment information from soil, the interior of greenhouse, and the exterior of greenhouse. To verify the good capability of our system, we implemented several GUI interface corresponding desktop. web, and PDA mobile platform based on real greenhouse model. Finally, we can confirm that our system work well prediction and management of pest of garden products in greenhouse based on several platforms.

• 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 Society of Computer and Information
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• v.24 no.8
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• pp.37-43
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• 2019

The existing smart farm technology has been systematized for the mass production rather than the consumer. There are many problems such as economical aspect to apply to actual rural environment due to aging. The purpose of this study is to apply smart farm technology based on the applicability of population aged in rural areas. Due to the heat wave, the crops in general greenhouse cultivation facilities suffered from damage such as sunlight damage. To minimize such damage, adjust the temperature and humidity environment or install a light-shielding film. However, the workers in the rural areas are aging and the elderly who are farming alone have a lot of difficulties in doing so. In the case of people with weak physical strength, there is a danger that they may lead to safety accidents when carrying heavy loads. In this paper, we propose 'Smart Palm capable of automatic transportation function', applying small smart vehicles that follow workers to existing smart farms to improve and prevent these problems. It is a smart farm that performs the control functions of the existing smart greenhouse environment, installs the rail for each trough, and has a vehicle that follows the worker. The smart app can directly control the greenhouse and the vehicle remotely manually.

• Journal of Bio-Environment Control
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• v.28 no.3
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• pp.225-233
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• 2019

In the summer season, natural ventilation is commonly used to reduce the inside air temperature of greenhouse when it rises above the optimal level. The greenhouse shape, vent design, and position play a critical role in the effectiveness of natural ventilation. In this study, computational fluid dynamics (CFD) was employed to investigate the effect of different roof vent designs along with side vents on the buoyancy-driven natural ventilation. The boussinesq hypothesis was used to simulate the buoyancy effect to the whole computational domain. RNG K-epsilon turbulence model was utilized, and a discrete originates (DO) radiation model was used with solar ray tracing to simulate the effect of solar radiation. The CFD model was validated using the experimentally obtained greenhouse internal temperature, and the experimental and computed results agreed well. Furthermore, this model was adopted to compare the internal greenhouse air temperature and ventilation rate for seven different roof vent designs. The results revealed that the inside-to-outside air temperature differences of the greenhouse varied from 3.2 to $9.6^{\circ}C$ depending on the different studied roof vent types. Moreover, the ventilation rate was within the range from 0.33 to $0.49min^{-1}$. Our findings show that the conical type roof ventilation has minimum inside-to-outside air temperature difference of $3.2^{\circ}C$ and a maximum ventilation rate of $0.49min^{-1}$.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.152-162
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• 2022

This study developed simulation model for predicting the greenhouse interior environment using artificial intelligence machine learning techniques. Various methods have been studied to predict the internal environment of the greenhouse system. But the traditional simulation analysis method has a problem of low precision due to extraneous variables. In order to solve this problem, we developed a model for predicting the temperature inside the greenhouse using machine learning. Machine learning models are developed through data collection, characteristic analysis, and learning, and the accuracy of the model varies greatly depending on parameters and learning methods. Therefore, an optimal model derivation method according to data characteristics is required. As a result of the model development, the model accuracy increased as the parameters of the hidden unit increased. Optimal model was derived from the GRU algorithm and hidden unit 6 (r² = 0.9848 and RMSE = 0.5857℃). Through this study, it was confirmed that it is possible to develop a predictive model for the temperature inside the greenhouse using data outside the greenhouse. In addition, it was confirmed that application and comparative analysis were necessary for various greenhouse data. It is necessary that research for development environmental control system by improving the developed model to the forecasting stage.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.29-37
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• 2012

An experiment for an optimized automatic greenhouse environment in a flower farming greenhouse by building a ubiquitous sensor network with various sensors was conducted and the results were evaluated. And various culturing environmental information and data in the greenhouse were collected and analyzed. Then, the greenhouse was designed to maintain the best culturing environment on the basis of existing recommended optimized figures. By measuring the growth of the crops in the greenhouse, A system which controls facilities in the greenhouse to maintain the best culturing environment in accordance with change in the environment was analyzed.Computer simulation result proced that we discovered that controlling the facilities and the artificial light source increased production, enhanced quality, reduced labor and heating cost immensely. The experiment has proved that the u-flower farming system can maximize the income of farm families by sending warning messages to users of this system when weather suddenly changes so that users may cope with such changes and maintain the best culturing environment.

• Journal of Bio-Environment Control
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• v.14 no.2
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• pp.76-82
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• 2005

Evaporative cooling pad system is one of the main cooling methods in greenhouses and its efficiency is very high. However, it has some disadvantages such as greenhouse temperature distributions are not uniform and installation cost is expensive. In this study, a CFD simulation model f3r predicting the air temperature distribution in the fan and fad cooling greenhouse was developed. The model was calibrated and validated against experimental data and a good fit was obtained. The influence of different outside wind, fan and pad height, ventilation rate, shading, and greenhouse length, were then examined. In order to reduce the internal temperature gradients, it is desired that the prevail wind direction and the fan and pad heights are considered. The simulation indicates that high ventilation rates and shading contribute to reduce the temperature gradients in the fan and pad cooling greenhouse. In order to maintain the desired greenhouse temperature, the pad-to-fan distance should be restricted according to the design climate conditions, shading and ventilation rates. The developed CFD model can be a useful tool to evaluate and design the fan and pad systems in the greenhouses with various configurations.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1519-1527
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• 2012

In this paper, we have implemented Green House automation system. The system should be kept in optimal condition in real-time by checking the greenhouse environmental conditions in the greenhouse. In addition, it can be converted to temporarily the necessary equipment by converting to manual mode in the environment you want. Environmental data collected from the greenhouse is sent to your computer monitor, as well as it support the web-based system to enable immediate control through the web. Users can view the situation of the greenhouse in real time by using a web-based system and maintain automation features by deciding specified conditions for a greenhouse environment.

• International Journal of Highway Engineering
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• v.18 no.1
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• pp.23-31
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• 2016

PURPOSES : This study aimed to offer a greenhouse gases table to assist a road designer in calculating the greenhouse gases for a road environment when making a decision about an alternative road. METHODS : This study developed an operation mode table of greenhouse gases using the MOVES program. Similar factors for Korean vehicles and fuels are reflected in the MOVES program, which was made in the USA. Finally, a paired t-test was conducted to calculate the site data and MOVES data. Through these studies, a methodology was suggested for calculating carbon emissions based on various types of roads alignments. RESULTS : The site results for a passenger truck on the road were statistically significant when the vehicle speed was above 65 km/h. However, a future study will consider factors for various road alignments and vehicles. CONCLUSIONS : This study will contribute to the theoretical basis for reducing carbon emissions from roads by helping road designers make decisions about road alternatives in terms of the road environment.

• Elastomers and Composites
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• v.55 no.2
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• pp.114-119
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• 2020

The effect of a greenhouse-covering material on its indoor environment and on the characteristics of cherry tomatoes grown in it was investigated. The conventional polyethylene (PE) film on the greenhouse roof was replaced by a polycarbonate (PC) sheet, while maintaining the main structural frame intact. Color changes and the formation of water droplets on the PC surface were avoided by applying coextrusion and coating layers. When compared to the PE greenhouse, the PC greenhouse enabled increased light transmittance and thus a higher indoor temperature during both summer and winter. The thermal insulating property of the PC sheet effectively reduced the heating loss by approximately 55% during winter. The cherry tomatoes grown in the PC greenhouse exhibited superior fruit characteristics in terms of size, weight, and sugar content. The total amount of cherry tomatoes produced per unit area (1,000 ㎡) in the PC greenhouse was found to be greater by approximately 19% compared to that in the PE greenhouse.