• Title/Summary/Keyword: Smart-farm

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A Study on the Patent Trend of 'Smart Farm' in Domestic through Network Analysis (네트워크 분석을 통한 국내 '스마트 팜' 특허 동향 연구)

  • Min, Kyong-Bin;Park, Hong-Jin
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.15 no.5
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    • pp.413-422
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    • 2022
  • Smart farms are receiving a lot of attention as a way to solve the chronic labor shortage and aging problems in agriculture. The smart farm industry, called the 6th industrial revolution, needs to strengthen its competitiveness. In order to apply innovative IT technology to agriculture, it is important to collect and analyze information about prior research or patents. This paper examines smart farm patent trends through 5,789 patent data related to smart farm using the domestic patent information search service(KIPRIS). This paper examines the domestic patent trends of smart farm information through keyword network, ego network, simultaneous appearance network, and bigram network analysis. As a result of network analysis related to smart farm patents, patents related to smart farm systems and control technologies were the most common. This paper can provide help in setting the direction of future smart farm-related patent research.

Hardware-in-the-loop Simulation Method for a Wind Farm Controller Using Real Time Digital Simulator

  • Kim, Gyeong-Hun;Kim, Jong-Yul;Jeon, Jin-Hong;Kim, Seul-Ki;Kim, Eung-Sang;Lee, Ju-Han;Park, Minwon;Yu, In-Keun
    • Journal of Electrical Engineering and Technology
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    • v.9 no.5
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    • pp.1489-1494
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    • 2014
  • A hardware-in-the-loop simulation (HILS) method for a wind farm controller using a real time digital simulator (RTDS) is presented, and performance of the wind farm controller is analyzed. A 100 MW wind farm which includes 5 MW wind power generation systems (WPGS) is modeled and analyzed in RSCAD/RTDS. The wind farm controller is implemented by using a computer, which is connected to the RTDS through transmission control protocol/internet protocol (TCP/IP). The HILS results show the active power and power factor of the wind farm, which are controlled by the wind farm controller. The proposed HILS method in this paper can be effectively utilized to validate and test a wind farm controller under the environment in practice without a real wind farm.

Development of the Insect Smart Farm System for Controlling the Environment of Protaetia brevitarsis seulensis

  • Rho, Si-Young;Won, Jin-Ho;Lee, Jae-Su;Baek, Jeong-Hyun;Lee, Hyun-Dong;Kwak, Kang-Su
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.12
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    • pp.135-141
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    • 2019
  • In this study, the "Insect Smart Farm Air Conditioning System" is designed and proposed for the control of breeding environment of Protaetia brevitarsis seulensis larvae. The proposed "Insect Smart Farm Air Conditioning System" separates the breeding room from the air conditioning room. It is a system that creates an environment optimized for breeding and distributes it into a breeding room. When controlling the environment through air-conditioning and humidifiers in insect farms, temperature and humidity vary from part of the breeding room to part. The solution to the problem can be suggested as a solution to the difficulty of producing white-spotted flower mounds of uniform size and weight when selling edible insects. By using the "Insect Smart Farm Air Conditioning System," the temperature difference can be reduced by 6℃ and the humidity difference by 24.7% compared to the environmental control of existing insect farms. The temperature and humidity of different parts of the breeding room were improved. Provide the optimal environment of Protaetia brevitarsis seulensis larvae at all times and ensure uniform CO2 concentration. It can be expected to increase output through annual production and increase income for insect farmers. The proposed "Insecting Smart Farm Air Conditioning System" also controls the set temperature, humidity and CO2. Environmental control of the breeding of other edible insects and the reproduction of mushrooms that require environmental control in breeding or breeding will also be possible.

Security Vulnerability and Countermeasures in Smart Farm (스마트 팜에서의 보안 취약점 및 대응 방안에 관한 연구)

  • Chae, Cheol-Joo;Han, Sang-Kyun;Cho, Han-Jin
    • Journal of Digital Convergence
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    • v.14 no.11
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    • pp.313-318
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    • 2016
  • Recently, the smart farm development using a PC and smart phone to manag the farm for improving competitiveness is in progress. In the smart farm, by using the various ICT technology including RFID, Wi-Fi, ZigBee, Wireless LAN, and etc., the growing environment of the crop and animals can be managed with the remote. By using the network including not only the TCP/IP based wired network but also ZigBee, Wireless LAN, and etc., each of the devices installed in the smart farm transmits the growing environment data to the server. So, smart farms have information and network security vulnerability. Therefore, we propose the method that analyzes the security vulnerability which can begenerated in the smart farm and user authentication method.

A Comparative Study Between Linear Regression and Support Vector Regression Model Based on Environmental Factors of a Smart Bee Farm

  • Rahman, A. B. M. Salman;Lee, MyeongBae;Venkatesan, Saravanakumar;Lim, JongHyun;Shin, ChangSun
    • Smart Media Journal
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    • v.11 no.5
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    • pp.38-47
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    • 2022
  • Honey is one of the most significant ingredients in conventional food production in different regions of the world. Honey is commonly used as an ingredient in ethnic food. Beekeeping is performed in various locations as part of the local food culture and an occupation related to pollinator production. It is important to conduct beekeeping so that it generates food culture and helps regulate the regional environment in an integrated manner in preserving and improving local food culture. This study analyzes different types of environmental factors of a smart bee farm. The major goal of this study is to determine the best prediction model between the linear regression model (LM) and the support vector regression model (SVR) based on the environmental factors of a smart bee farm. The performance of prediction models is measured by R2 value, root mean squared error (RMSE), and mean absolute error (MAE). From all analysis reports, the best prediction model is the support vector regression model (SVR) with a low coefficient of variation, and the R2 values for Farm inside temperature, bee box inside temperature, and Farm inside humidity are 0.97, 0.96, and 0.44.

Design of Smart Farm with Automatic Transportation Function

  • Hur, Hwa-ra;Park, Seok-Gyu;Park, Myeong-Chul
    • 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.

A Study on the Implementation of Raspberry Pi Based Educational Smart Farm

  • Min-jeong Koo
    • International journal of advanced smart convergence
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    • v.12 no.4
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    • pp.458-463
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    • 2023
  • This study presents a paper on the implementation of a Raspberry Pi-based educational smart farm system. It confirms that in a real smart farm environment, the control of temperature, humidity, soil moisture, and light intensity can be smoothly managed. It also includes remote monitoring and control of sensor information through a web service. Additionally, information about intruders collected by the Pi camera is transmitted to the administrator. Although the cost of existing smart farms varies depending on the location, material, and type of installation, it costs 400 million won for polytunnel and 1.5 billion won for glass greenhouses when constructing 0.5ha (1,500 pyeong) on average. Nevertheless, among the problems of smart farms, there are lax locks, malfunctions to automation, and errors in smart farm sensors (power problems, etc.). We believe that this study can protect crops at low cost if it is complementarily used to improve the security and reliability of expensive smart farms. The cost of using this study is about 100,000 won, so it can be used inexpensively even when applied to the area. In addition, in the case of plant cultivators, cultivators with remote control functions are sold for more than 1 million won, so they can be used as low-cost plant cultivators.

A Study on the Implementation of Smart Farm Environment Control System Using Unity and Photon (Unity와 Photon을 활용한 스마트 팜 환경 제어 시스템 구현에 관한 연구)

  • Jung, Hyeon Ji;Lee, Wan Bum
    • Journal of the Semiconductor & Display Technology
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    • v.20 no.1
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    • pp.104-107
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    • 2021
  • Unity programs are largely recognized as game development tools. However, it has many functions built in, so it can be applied to various fields as well as game development. Therefore, in this paper, we propose a smart farm environmental control program using Unity and Photon. The proposed program has vast compatibility that is not limited to specific devices, and it is very easy to build network systems for remote control. In addition, the proposed programs were installed on various devices such as pc and smartphones, making it easy to control the smart farm environment system. Through experiments, it was confirmed that data transmission and reception between Windows and Android, other operating system environments, and that smart farm systems were operating normally.