• Journal of the Korea Convergence Society
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• v.8 no.9
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• pp.339-345
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• 2017

Recently, agriculture and the environment has changed dramatically due to global warming and abnormal weather. In particular, it is necessary to develop new agricultural techniques according to transforming the growing environment of agricultural crops. Therefore, "Smart Farm" building technology for controlling agricultural environment and improving efficiency for ICT technology development has recently been introduced. However, in reality, systematic and objective evaluation items are absent at various levels and management levels that affect the management environment of the smart farm. In this research, it derived the importance index among the factors associated with Smart Farm technology by AHP method. As a result, in order to evaluate comprehensive operation and management of the smart farm, the two evaluation fields(sensor device and control/information management system) were selected as the top evaluation items. These results mean that system that can detect the growth environment information of agricultural crops and control the growing environment is more important than anything, when smart farm is applied. It is judged that the results of this research can be used as basic data for making evaluation indicators associated with the introduction of smart palm technology in the future.

• Smart Media Journal
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• v.13 no.2
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• pp.16-22
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• 2024

Greenhouse provides opportunities to have big yield effectively and efficiently. However, many resources are required, such as fertigation, a kind of solution of nutrient. Resources supply is essential to cultivate crops. Inadequate supply will hinder plant growth whereas the surplus results in waste. In this paper, we are especially interested in the fertigation supply. Further, excess fertigation leads to drainage which is difficult to purify and threatens the environment. To address this challenge, we aim to predict the desired amount of fertigation. To achieve this objective, we first establish a prototype to record the climate conditions inside a rose greenhouse using Internet of Things sensors. Simultaneously, the desired fertigation amount is obtained with the help of weight scale and historical data of fertigation supply and drainage. Second, a method is proposed to predict the desired fertigation by taking the sensors' data as input, with a time-series model. Extensive experimental results suggest the potential of our objective and method. To be specific, our method achieves an average MAE 0.032 in the validation datasets.

• Journal of Mushroom
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• v.16 no.3
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• pp.155-161
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• 2018

In this study, we analyze the growth environment using smart farm technology in order to develop the optimal growth model for the precision cultivation of the bottle-grown oyster mushroom 'Suhan'. Experimental farmers used $88m^2$ of bed area, 2 rows and 5 columns of shelf shape, 5 hp refrigerator, 100T of sandwich panel for insulation, 2 ultrasonic humidifiers, 12 kW of heating, and 5,000 bottles for cultivation. Data on parameters such as temperature, humidity, carbon dioxide concentration, and illumination, which directly affect mushroom growth, were collected from the environmental sensor part installed at the oyster mushroom cultivator and analyzed. It was found that the initial temperature at the time of granulation was $22^{\circ}C$ after the scraping, and the mushroom was produced and maintained at about $25^{\circ}C$ until the bottle was flipped. On fruiting body formation, mushrooms were harvested while maintaining the temperature between $13^{\circ}C$ and $15^{\circ}C$. Humidity was approximately 100% throughout the growth stage. Carbon dioxide concentration gradually increased until 3 days after the beginning of cultivation, and then increased rapidly to approximately 2,600 ppm. From the 6th day, $CO_2$ concentration was gradually decreased through ventilation and maintained at 1,000 ppm during the harvest. Light was not provided at the initial stage of oyster mushroom cultivation. On the $3^{rd}$ and $4^{th}$ day, mushrooms were irradiated by 17 lux light. Subsequently, the light intensity was increased to 115-120 lux as the growth progressed. Fruiting body characteristics of 'Suhan' cultivated in a farmhouse were as follows: Pileus diameter was 30.9 mm and thickness was 4.5 mm; stipe thickness was 11.0 mm and length was 76.0 mm; stipe and pileus hardness was 0.8 g/mm and 2.8 g/mm, respectively; L values of the stipe and pileus were 79.9 and 52.3, respectively. The fruiting body yield was 160.2 g/850 ml, and the individual weight was 12.8 g/10 unit.

• 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 the Korea Society of Computer and Information
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• v.27 no.9
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• pp.49-57
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• 2022

Currently, the problem of food shortage is emerging in our society due to climate problems and an increase population in the world. As a solution to this problem, we propose a multi-remote control smart farm that combines artificial intelligence (AI) and information and communication technology (ICT) technologies. The proposed smart farm integrates ICT technology to remotely control and manage crops without restrictions in space and time, and to multi-control the growing environment of crops. In addition, using Arduino and deep-learning technology, a smart farm capable of multiple control through a smart-phone application (APP) was proposed, and Ai technology with various data securing and diagnosis functions while observing crop growth in real-time was included. Various sensors in the smart farm are controlled by using the Arduino, and the data values of the sensors are stored in the built database, so that the user can check the stored data with the APP. For multiple control for multiple crops, each LED, COOLING FAN, and WATER PUMP for two or more growing environments were applied so that the user could control it conveniently. And by implementing an APP that diagnoses the growth stage through the Tensor-Flow framework using deep-learning technology, we developed an application that helps users to easily diagnose the growth status of the current crop.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.2
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• pp.390-396
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• 2015

The drastic growth of mobile communication and spreading of smart phone make the significant attention on Location Based Service. The one of most important things for vitalizations of LBS is the accurate estimating position for mobile object. Focusing on an image sensor deployed in smart phone, we develop a LED based positioning estimation framework. The developed approaches can strengthen the advantages of independent indoor applicability of LED. The estimation of LED based positioning is effectively applied to any indoor environment. We put a focus especially on the algorithmic framework. of image processing of smart phone. From LED lighting, we can obtain a typical signal image which contains the unique positioning information. Furthermore test-bed based on smart phone platform is practically developed and all data have been harvested from the actual measurement of test indoor area. This can approve the practical usefulness of proposed framework.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.2
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• pp.143-150
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• 2013

Recently, environmental issues such as climate warming, ozone layer depletion, reduction of tropical forests and desertification are emerging as global environmental problems beyond national problems. And international attention and effort have been carried out in many ways to solve these problems. In this study, the growth of green was calculated quantitatively using the technique of remote sensing and temperature change was figured out through temperature extraction in the city. The land-cover changes and thermal changes for research areas were analyzed using Landsat TM images on May 2002 and May 2009. Surface temperature distribution was calculated using spectral degree of brightness of Band 6 that was Landsat TM thermal infrared sensor to extract the ground surface temperature in the city. As a result of research, the area of urban green belt was increased by $2.87km^2$ and the ground surface temperature decreased by $0.6^{\circ}C{\sim}0.8^{\circ}C$ before and after tree planting projects. Henceforth, if the additional study about temperature of downtown is performed based on remote sensing and measurement data, it will contribute to solve the problems about the urban environment.

• The KIPS Transactions:PartC
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• v.18C no.3
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• pp.167-178
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• 2011

As the growth of ubiquitous services, various types of ad hoc networks have emerged. In particular, wireless sensor networks (WSN) and mobile ad hoc networks (MANET) are widely known ad hoc networks, but there are also other kinds of wireless ad hoc networks in which the characteristics of the aforementioned two network types are mixed together. This paper proposes a variant of the Low Energy Adaptive Cluster Hierarchy (LEACH) routing protocol modified to be suitable in such a combined network environment. That is, the proposed routing protocol provides node detection and route discovery/maintenance in a network with a large number of mobile sensor nodes, while preserving node mobility, network connectivity, and energy efficiency. The proposed routing protocol is implemented with a multi-hop multi-path algorithm, a topology reconfiguration technique using node movement estimation and vibration sensors, and an efficient path selection and data transmission technique for a great many moving nodes. In the experiments, the performance of the proposed protocol is demonstrated by comparing it to the conventional LEACH protocol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5276-5298
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• 2019

Internet of Things (IoT) based sensor networks have gained unprecedented popularity in recent years. With the exponential explosion of the objects (sensors and mobiles), the bandwidth and the speed of data transmission are dwarfed by the anticipated emergence of IoT. In this paper, we propose a novel heterogeneous IoT model integrated the power line communication (PLC) and WiFi network to increase the network capacity and cope with the rapid growth of the objects. We firstly propose the mean transmission delay calculation algorithm based the 3D Markov chain according to the multi-priority of the objects. Then, the attractor selection algorithm, which is based on the adaptive behavior of the biological system, is exploited. The combined the 3D Markov chain and the attractor selection model, named MASM, can select the optimal path adaptively in the heterogeneous IoT according to the environment. Furthermore, we verify that the MASM improves the transmission efficiency and reduce the transmission delay effectively. The simulation results show that the MASM is stable to changes in the environment and more applicable for the heterogeneous IoT, compared with the other algorithms.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.409-415
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• 2022

Plant growth and development are also affected by root-zone environment. Therefore, it is important to consider the variables of the root-zone environment when establishing an irrigation strategy. The purpose of this study is to analyze the relationship between the volumetric moisture content (VWC), Bulk EC (ECb), and Pore EC (ECp) used by plant roots using FDR sensors in two types of rockwool media with different water transmission characteristics, using the method above this was used to establish a method for collecting and correcting available root-zone environmental data. For the experiment, two types of rockwool medium (RW1, RW2) with different physical characteristics were used. The moisture content (MC) and ECb were measured using an FDR sensor, ECp was measured after extracting the residual nutrient solution from the medium using a disposable syringe in the center of the medium at a volumetric moisture content (VWC) of 10-100%. Then, ECb and ECp are measured by supplying nutrient solution having different concentration (distilled water, 0.5-5.0) to two types of media (RW1, RW2) in each volume water content range (0 to 100%). The relationship between ECb and ECp in RW1 and RW2 media is best suited for cubic polynomial. The relationship between ECb and ECp according to volume moisture content (VWC) range showed a large error rate in the low volume moisture content (VWC) range of 10-60%. The correlation between the sensor measured value (ECb) and the ECp used by plant roots according to the volumetric water content (VWC) range was the most suitable for the Paraboloid equation in both media (RW1, RW2). The coefficient of determination the calibration equation for RW1 and RW2 media were 0.936, 0.947, respectively.