• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.151-155
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• 2024

This project is designed with the aim to facilitate the farmer or gardener to engage in green house systems and to improve agricultural technology. In order to reduce continuous monitoring of the soil parameters, excess time consumption for the farmers and excessive usage of water, "Smart irrigation and temperature control for a greenhouse system" has been developed. There are two different ways to irrigate the land namely traditional irrigation methods and modern irrigation methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.318-325
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• 2019

Recently, research and development on agricultural robots have been on the rise as the interest in smart farming has increased. Robots used in smart greenhouses should be taken into account with the working characteristics and growing environment. This study examined cleaning robots developed through the environmental analysis of smart greenhouses. This study assessed the evaluation method considering the requirements of the pest control robot applicable to the smart greenhouse. The performance and quality assessment criteria were established to conduct tests through the requirements of robots. The required functions and goals of the pest control robot were derived by referring to the robot-related standards. A driving and working ability test was conducted to assess the performance of the robot. The driving test was conducted on the driving performance of the robot and the work capability was tested on the pest control performance. In addition, a durability test was conducted to assess the quality of the robot. The required factors for smart greenhouse robots were derived from the test results. The study results are expected be a standard for an evaluation of a variety of robots for applications to smart greenhouses.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.5 no.5
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• pp.471-479
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• 2015

This study was conducted to make use of Korea Meteorological Administration(KMA)'s Automatic Weather Station(AWS) data to operate smart green greenhouse. A Web-based KMA AWS data receiving system using JAVA and APM_SETUP 8 on windows 7 platform was developed. The system was composed of server and client. The server program was developed by a Java application to receive weather data from the KMA every 30 minutes and to send the weather data to smart greenhouse. The client program was developed by a Java applets to receive the KMA AWS data from the server every 30 minutes through communicating with the server so that smart greenhouse could recognize the KMA AWS data as the ambient weather information. This system was evaluated by comparing with local weather data measured by Inc. Ezfarm. In case of ambient air temperature, it showed some difference between virtual data and measured data. But, the average absolute deviation of the difference has a little difference as less than 2.24℃. Therefore, the virtual weather data of the developed system was considered available as the ambient weather information of the smart greenhouse.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.75-84
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• 2021

As the weather changes become frequent, weather disasters are increasing, causing more damage to plastic greenhouses. Among the damage caused by various disasters, damage by snow to the greenhouse takes a relatively long time, so if an alarm system is properly prepared, the damage can be reduced. Existing greenhouse design standards and snow warning systems are based on snow depth. However, even in the same depth, the load on the greenhouse varies depending on meteorological characteristics and snow density. Therefore, this study aims to secure the structural safety of greenhouses by developing sensors that can directly measure snow loads, and analysing the warning criteria for load using a stochastic model. Markov chain was applied to estimate the failure probability of various types of greenhouses in various regions, which let users actively cope with heavy snowfall by selecting an appropriate time to respond. Although it was hard to predict the precise snow depth or amounts, it could successfully assess the risk of structures by directly detecting the snow load using the developed sensor.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.61-74
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• 2021

Agriculture is most closely related to weather, and the government pursues stable food production by weather research. However, abnormal weather conditions have occurred frequently around the world in recent years, and stable food production has been threatened. Among them, heavy snow in winter tends to increase in frequency and size, which causes serious damage to greenhouses. Therefore, it is imperative to build a system reflecting various demands to reduce the damage to agricultural facilities caused by heavy snow. A business model can realize this as a way of commercialization, however, no suitable model has been presented to date. Therefore, this study aims to design a representative business model that can establish a safety system by distributing a greenhouse disaster prevention warning system for heavy snow to farms.

• Korean journal of applied entomology
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• v.59 no.1
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• pp.55-64
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• 2020

Smart greenhouses are primarily used for growing fruits and vegetables, such as sweet peppers, tomatoes, strawberries. Although the number of smart greenhouses has been increasing exponentially, no studies have been performed to evaluate the state of smart greenhouses in Korea. Therefore, this study was conducted to determine current state of smart greenhouses with regard to greenhouse specifications, crop growing methods, pests, and user satisfaction in Korea. Contact information for smart greenhouses was provided by the officials of local agricultural research and extension services. This survey was conducted by visiting each greenhouse. Results showed that approximately 50% of surveyed smart greenhouses were between 3,300 ㎡ and 6,600 ㎡. The most frequently chosen method for pest control was chemical pesticides (97.1%). Powdery mildew and gray mold comprised 54.4% and 33.8% of the crop diseases, respectively. All tomato greenhouse farmers considered whiteflies the most problematic pest. In contrast, 76.5% and 70.6% of sweet pepper farmers believed thrips and aphids posed significant threats, respectively. The mean satisfaction score was 7.5 out of 10 points, with 10 being "extremely satisfied". These results will aid in decision making with respect to the management of current smart greenhouses and the design of future smart farms in Korea.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.278-286
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• 2021

In this study, based on the Computational Fluid Dynamics (CFD) simulation model developed through previous study, inner environmenct of the modified glass greenhouse was predicted. Also, suggested the optimal shape of the greenhouse and location of the heat exchangers for heat energy management of the greenhouse using the developed model. For efficient heating energy management, the glass greenhouse was modified by changing the cross-section design and the location of the heat exchanger. The optimal cross-section design was selected based on the cross-section design standard of Republic of Korea's glass greenhouse, and the Fan Coil Unit(FCU) and the radiating pipe were re-positioned based on "Standard of greenhouse environment design" to enhance energy saving efficiency. The simulation analysis was performed to predict the inner temperature distribution and heat transfer with the modified greenhouse structure using the developed inner environment prediction model. As a result of simulation, the mean temperature and uniformity of the modified greenhouse were 0.65℃, 0.75%p higher than those of the control greenhouse, respectively. Also, the maximum deviation decreased by an average of 0.25℃. And the mean age of air was 18 sec. lower than that of the control greenhouse. It was confirmed that efficient heating energy management was possible in the modified greenhouse, when considered the temperature uniformity and the ventilation performance.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.135-135
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• 2017

Greenhouse have been developed to provide the plants with good environmental conditions for cultivation crop, two major factors of which are the inside air temperature and humidity. The inside temperature are influenced by the heating systems, ventilators and for systems among others, which in turn are geverned by some type of controller. Likewise, humidity environment is the result of complex mass exchanges between the inside air and the several elements of the greenhouse and the outside boundaries. Most of the existing models are based on the energy balance method and heat balance equation for modelling the heat and mass fluxes and generating dynamic elements. However, greenhouse are classified as complex system, and need to make a sophisticated modeling. Furthermore, there is a difficulty in using classical control methods for complex process system due to the process are non linear and multi-output(MIMO) systems. In order to predict the time evolution of conditions in certain greenhouse as a function, we present here to use of recurrent neural networks(RNN) which has been used to implement the direct dynamics of the inside temperature and inside humidity of greenhouse. For the training, we used algorithm of a backpropagation Through Time (BPTT). Because the environmental parameters are shared by all time steps in the network, the gradient at each output depends not only on the calculations of the current time step, but also the previous time steps. The training data was emulated to 13 input variables during March 1 to 7, and the model was tested with database file of March 8. The RMSE of results of the temperature modeling was $0.976^{\circ}C$, and the RMSE of humidity simulation was 4.11%, which will be given to prove the performance of RNN in prediction of the greenhouse environment.

• Journal of Information Technology Services
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• v.11 no.4
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• pp.123-134
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• 2012

Recently, The Bali Road Map was approved, as it demands that developing countries should also have the responsibility of greenhouse gas reduction from 2013. This suggests that the greenhouse gas and environment should be controlled across industry sectors. Accordingly, this study was conducted to identify the application and effects of the IT convergence technology to the smart farm and realize the low-carbon green industry in Korea. The smart farm technologies within and outside of Korea were comparatively analyzed for the low-carbon green industry policy. The study subjects were determined to propose the necessity of the study efficiently. First, the studies on the smart farm for low-carbon green industry policy were examined. Second, the suitable IT technology for the smart farm as well as the effect and the improvement plan of the IT technology-based smart farm system were examined. This study now aims to promote the low-carbon green industry policy and IT convergence technology and job creation. These will be achieved by providing the plan for linking the system simulator organization with the low-carbon green industry policy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.509-512
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• 2016

The standard of the greenhouse control system defines the components in applying IT technologies to a greenhouse and specifies the requirements and the architecture for the technological issues. The system collects information for the growth management of corps and can control the facilities promoting the optimal growth environments in greenhouse. This system includes the growth environment management service, the growth environment control service, and etc. 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, suggest to standard functional model and standardization items for the smart farming based on network.