• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.583-589
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• 2020

Recently, the utility of UAS (Unmanned Aerial System) for a smart farm using various sensors and ICT (Information & Communications Technology) is expected. In particular, it has proven its effectiveness as an outdoor crop monitoring method through various indices and is being studied in various fields. This study analyzes damage to crops caused by natural disasters and measures the damage area of rice plants. To this end, data is acquired using BG-NIR (Blue Green_Near Infrared Red) and RGB sensors, and image analysis and NDWI (Normalized Difference Water Index) index performed to review crop damage caused by in the rainy season. Also, point cloud data based on image analysis is generated, and damage is measured by comparing data before and after the typhoon through an inspection map. As a result of the study, the growth and rainy season damage of rice was examined through NDWI index analysis, and the damage area caused by typhoon was measured by analysis of the inspection map.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.628-636
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• 2021

This paper contains the implementation and performance evaluation results of a system that collects environmental data at the time when the wild animal intrusion occurred at farms and then predicts future wild animal intrusions through a machine learning-based Vector Autoregression(VAR) model. To collect the data for intrusion prediction, an IoT-based hardware prototype was developed, which was installed on a small farm located near the school and simulated over a long period to generate intrusion events. The intrusion prediction service based on the implemented VAR model provides the date and time when intrusion is likely to occur over the next 30 days. In addition, the proposed system includes the function of providing real-time notifications to the farmers mobile device when wild animals intrusion occurs in the farm, and performance evaluation was conducted to confirm that the average response time was 7.89 seconds.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.440-444
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• 2018

Purpose: Cloud-computing technology has several advantages, including maintenance, management, accessibility, and computing power. A greenhouse-control system utilizing these advantages was developed using a private cloud-computing system. Methods: A private cloud needs a collection of servers and a suite of software tools to monitor and control cloud-computing resources. In this study, a server farm, operated by OpenStack as a cloud platform, was constructed using servers, and other network devices. Results: The greenhouse-control system was developed according to the fundamental cloud service models: infrastructure as a service, platform as a service, and software as a service. This system has four additional advantages - security, control function, public data use, and data exchange. There are several considerations that must be addressed, such as service level agreement, data ownership, security, and the differences between users. Conclusions: When the advantages are utilized and the considerations are addressed, cloud-computing technology will be beneficial for agricultural use.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.130-136
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• 2020

There are many problems that occur currently in agriculture industries. The problems such as unexpected of changing weather condition, lack of labor, dry soil were some of the reasons that may cause the growth of the plants. Condition of the weather in local area is inconsistent due to the global warming effect thus affecting the production of the crops. Furthermore, the loss of farm labor to urban manufacturing jobs is also the problem in this industry. Besides, the condition for the plant like air humidity, air temperature, air quality index, and soil moisture are not being recorded automatically which is more reason for the need of implementation system to monitor the data for future research and development of agriculture industry. As of this, we aim to provide a solution by developing IoT-based platform along with the irrigation for increasing crop quality and productivity in agriculture field. We aim to develop a smart garden system environment which the system is able to auto-monitoring the humidity and temperature of surroundings, air quality and soil moisture. The system also has the capability of automating the irrigation process by analyzing the moisture of soil and the climate condition (like raining). Besides, we aim to develop user-friendly system interface to monitor the data collected from the respective sensor. We adopt an open source hardware to implementation and evaluate this research.

• Journal of Internet of Things and Convergence
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• v.2 no.3
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• pp.31-35
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• 2016

IoT technologies have been rapidly developed in recent years, and applied to many industries. In the field of fisheries, the water quality management system have been developed, helping in improving productivity and working environment. In this paper, we have designed the smart feeding system, interoperable with the water quality system, using LPWA network. LPWA network is an IoT network, which is appropriate to fish farms because of its wide area coverages and low power consumption. We expect this work to contribute to developing the aquaculture technology through the big data analysis with the accumulated data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.379-381
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• 2021

As information and communication technologies develop, many studies are being conducted to maintain an efficient production environment by applying network and computing technologies to existing production systems. Unlike classical control systems, these smart production systems need to collect data about the production environment in real time, and operate fluidly as it changes. In this paper, we present a measurement system that can collect data in real time through network-based sensors and respond effectively to environmental changes. We also proved this smart system can cope with external environmental changes and maintain an effective production environment.

• 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 Solar Energy Society
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• v.33 no.4
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• pp.23-30
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• 2013

This paper presents the determination method of the hybrid energy storage capacity for compensating the output of wind power when disconnecting from the grid. In the wind power output compensation, a lot of charging and discharging time with lithium-ion battery will be deteriorated the life time. And also, this fluctuation will cause some problems of the power quality and power system stability. To solve these kind of problems, many researchers in the world have been studied with BESS(Battery Energy Storage System) in the wind farm. But, BESS has the limitation of its output during very short term period, this means that it is difficult to compensate the very short term output of wind farm. Using the EDLC (Electric Double Layer Capacitor), it is possible to solve the problem. Installing the battery system in the wind farm, it will be possible to decrease the total capacity of BESS consisting of HESS (Hybrid Energy Storage System). This paper shows simulation results when not only BESS is connected to wind farm but also to HESS. To verify the proposed system, results of computer simulation using PSCAD/EMTDC program with actual output data of wind farms of Jeju Island will be presented.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.104-109
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• 2021

In the aftermath of the global pandemic that started in 2019, there have been many changes in the import/export and supply/demand process of agricultural products in each country. Amid these changes, the necessity and importance of each country's food self-sufficiency rate is increasing. There are several conditions that must accompany efficient agricultural activities, but among them, temperature is by far one of the most important conditions. For this reason, the need for high-accuracy climate data for stable agricultural activities is increasing, and various studies on climate prediction are being conducted in Korea, but data that can visually confirm climate prediction data for farmers are insufficient. Therefore, in this paper, we propose an artificial intelligence-based temperature prediction algorithm that can predict future temperature information by collecting and analyzing temperature data of farms in Gyeonggi-do in Korea for the last 10 years. If this algorithm is used, it is expected that it can be used as an auxiliary data for agricultural activities.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.389-396
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• 2020

In this paper, a cultivation traceability system to implement smart agriculture developed and implemented, and in particular, devised a system that manages the cultivation traceability of grains that are difficult to grow in smart farms. Mobile and web programs based on smart devices are designed, and the collected information is stored in a DB server and can be used as big data. In addition, real-time location information and agricultural activity information can be matched using an electronic map(Vworld) based on GIS/LBS applying GPS of a mobile device. By designing the cultivation traceability information DB required in the field, the farmhouse, farmers, and cultivation information were developed to make it easy for managers to use, and implemented mobile and web programs in the field. The system is expected to raise the quality and safety management capabilities to the next level in response to variables such as labor saving effect and climate change.