• Title/Summary/Keyword: Smart farming

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Analysis of the Present Status and Future Prospects for Smart Agriculture Technologies in South Korea Using National R&D Project Data

  • Lee, Sujin;Park, Jun-Hwan;Kim, EunSun;Jang, Wooseok
    • Journal of Information Science Theory and Practice
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    • v.10 no.spc
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    • pp.112-122
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    • 2022
  • Food security and its sovereignty have become among the most important key issues due to changes in the international situation. Regarding these issues, many countries now give attention to smart agriculture, which would increase production efficiency through a data-based system. The Korean government also has attempted to promote smart agriculture by 1) implementing the agri-food ICT (information and communications technology) policy, and 2) increasing the R&D budget by more than double in recent years. However, its endeavors only centered on large-scale farms which a number of domestic farmers rarely utilized in their farming. To promote smart agriculture more effectively, we diagnosed the government R&D trends of smart agriculture based on NTIS (National Science and Technology Information Service) data. We identified the research trends for each R&D period by analyzing three pieces of information: the regional information, research actor, and topic. Based on these findings, we could suggest systematic R&D directions and implications.

Assessing the adoption potential of a smart greenhouse farming system for tomatoes and strawberries using the TOA-MD model

  • Lee, Won Seok;Kim, Hyun Seok
    • Korean Journal of Agricultural Science
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    • v.47 no.4
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    • pp.743-752
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    • 2020
  • The purpose of this study was to estimate the economic evaluation of a smart farm investment for tomatoes and strawberries. In addition, the potential adoption rate of the smart farm was derived for different scenarios. This study analyzed the economic evaluation with the net present value (NPV) method and estimated the adoption potential of the smart farm with the trade-off analysis, minimum data (TOA-MD) model. The results were as follows: The analysis of the net present value shows that the smart farm investment for the two crops are economically feasible, and the minimum prices for the tomatoes and strawberries should be 1,179 and 3,797 won/kg to secure a sufficient economic feasibility for the smart farm investment. Next, the analysis of the potential adoption rates for smart farms through the TOA-MD model showed that when the support ratio for the adoption of a smart farm system was 50% and the price increase rates were, respectively, - 5, 2.5, 0, 2.5, and 5%, the conversion rates for tomato farms to switch to smart farms were 0.97, 1.78, 3.05, 4.91, and 7.47%, while the ratios of the strawberry farms to switch to smart farms were 0.12, 0.29, 0.65, 1.33, and 2.53%, respectively. This study has some known limitations, but it provides useful information on decision making about smart farm adoption and can contribute to government policies on smart farms.

Production Performance Prediction of Pig Farming using Machine Learning (기계학습기반 양돈생산성 예측방안)

  • Lee, Woongsup;Sung, Kil-Young;Ban, Tae-Won;Ham, Young Hwa
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.1
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    • pp.130-133
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    • 2020
  • Smart pig farm which is based on IoT has been widely adopted by many pig farmers. In order to achieve optimal control of smart pig farm, the relation between environmental conditions and performance metric should be characterized. In this study, the relation between multiple environmental conditions including temperature, humidity and various performance metrics, which are daily gain, feed intake, and MSY, is analyzed based on data obtained from 55 real pig farm. Especially, based on preprocessing of data, various regression based machine learning algorithms are considered. Through performance evaluation, we show that the performance can be predicted with high precision, which can improve the efficiency of management.

Blockchain and IoT Integrated Banana Plant System

  • Geethanjali B;Muralidhara B.L.
    • International Journal of Computer Science & Network Security
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    • v.24 no.2
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    • pp.155-157
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    • 2024
  • Internet of Things (IoT) integrated with the Blockchain is the state of the art for keen cultivation and agriculture. Recently the interest in agribusiness information is enlarging owing to the fact of commercializing the smart farming technology. Agribusiness information are known to be untidy, and experts are worried about the legitimacy of information. The blockchain can be a potential answer for the expert's concern on the uncertainty of the agriculture data. This paper proposes an Agri-Banana plant system using Blockchain integrated with IoT. The system is designed by employing IoT sensors incorporated with Hyperledger fabric network, aims to provide farmers with secure storage for preserving the large amounts of IoT and agriculture data that cannot be tampered with. A banana smart contract is implemented between farmer peer and buyer peer of two different organizations under the Hyperledger fabric network setup aids in secure transaction of transferring banana from farmer to buyer.

A Study on Modular Agricultural Robotic Platform for Upland (밭 노지 환경 주행을 위한 모듈형 농업 로봇 플랫폼에 대한 연구)

  • Cho, Yongjun;Woo, Seong Yong;Song, Su Hwan;Hong, Hyung Gil;Yun, Haeyong;Oh, Jang Seok;Kim, Junseong;Kim, Dong Woo;Seo, Kab Ho;Kim, Dae Hee
    • The Journal of Korea Robotics Society
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    • v.15 no.2
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    • pp.124-130
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    • 2020
  • This paper designed modular agricultural robotic platform capable of a variety of agricultural tasks to address the problems caused by a decline in agricultural populations and an increase in average age. We propose a modular robotic platform that can perform many tasks required in field farming by replacing only work modules with common robotic platforms. This platform is capable of steering while driving on four wheels in an upland environment where farm work is performed, and an attitude control module is attached to each drive module to control the attitude of the platform. In addition, the width of the platform is designed to be variable in order to operate in various ridges according to the crop cultivation method. Finally, we evaluated five items: variable width, gradient, attitude control angle, step and road speed in order to carry out the farming industry while maintaining a stable posture.

Design of Initial Decision-Making Support Interface for Crop Facility Cultivation (작물 시설재배 초기 의사결정 지원 인터페이스 설계)

  • Kim, Kuk-Jong;Cho, Yong-Yoon
    • Journal of Internet of Things and Convergence
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    • v.8 no.2
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    • pp.71-78
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    • 2022
  • Recently, the number of people wishing to return to farming is increasing, However, the lack of farming experience and management information of returnees is one of the main reasons for increasing the probability of agricultural failure. This study proposes an interface to support early facility cultivation management decision-making for returnees who want facility cultivation. The proposed interface is designed with UML(Unified Modeling Language) and provides key decision-making information such as land/crop suitability, land/facility costs, and management costs according to input data such as cultivation areas, selected crops, and cultivation types selected by the user. Through the proposed interface, facility cultivators can effectively and quickly acquire initial decision-making information for facility cultivation in the desired target area.

Smart Control System for Greenhouse Environment (시설원예용 스마트 환경 제어 시스템)

  • Kim, Eung-Kon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.5
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    • pp.907-914
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    • 2017
  • Recently, industrialization and automation for crops has enabled the development of smart farm technology over the world This is due to the need for the automation and convenience of the agricultural system to aging the population and reducing the labor force. In this system, the smart app can control the temperature and humidity that can be conveniently managed by the farmers. It is possible to check the status of the greenhouses in real time in the smartphone and maintain the optimum temperature and humidity, thereby helping to prevent pests and diseases, to grow crops, and to improve the labor force and productivity of farmers and fishermen.

Growth Monitoring for Soybean Smart Water Management and Production Prediction Model Development

  • JinSil Choi;Kyunam An;Hosub An;Shin-Young Park;Dong-Kwan Kim
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2022.10a
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    • pp.58-58
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    • 2022
  • With the development of advanced technology, automation of agricultural work is spreading. In association with the 4th industrial revolution-based technology, research on field smart farm technology is being actively conducted. A state-of-the-art unmanned automated agricultural production demonstration complex was established in Naju-si, Jeollanam-do. For the operation of the demonstration area platform, it is necessary to build a sophisticated, advanced, and intelligent field smart farming model. For the operation of the unmanned automated agricultural production demonstration area platform, we are building data on the growth of soybean for smart cultivated crops and conducting research to determine the optimal time for agricultural work. In order to operate an unmanned automation platform, data is collected to discover digital factors for water management immediately after planting, water management during the growing season, and determination of harvest time. A subsurface drip irrigation system was established for smart water management. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. Vegetation indices were collected using drones to find key factors in soybean production prediction. In addition, major growth characteristics such as stem length, number of branches, number of nodes on the main stem, leaf area index, and dry weight were investigated. By discovering digital factors for effective decision-making through data construction, it is expected to greatly enhance the efficiency of the operation of the unmanned automated agricultural production demonstration area.

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Research on Ways to Apply Smart Livestock Farming Based on Metaverse (메타버스 기반의 축사 스마트팜 적용 방안 연구)

  • YeonJae Oh
    • Smart Media Journal
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    • v.13 no.2
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    • pp.136-144
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    • 2024
  • In recent years, with the rapid development of IT technology and the aging of the population, various solutions to the labor shortage have emerged. In the livestock industry, there are an increasing number of management systems that utilize artificial intelligence technology. The Metaverse Smart Farm is a system that combines the digital virtual world with advanced agricultural technology. With this system, farmers can monitor the health of their animals in real time without having to visit the barns, and analyze the data collected through sensors and cameras for more efficient agricultural management. In addition, the barn environment can be adjusted through a remote control function, which is expected to reduce labor and revitalize the livestock industry.

Policy Direction for Smart Farming

  • 한국농식품정보과학회
    • Agribusiness and Information Management
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    • v.12 no.2
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    • pp.24-39
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    • 2021
  • As the number of fields adopting ICT (Information and Communication Technology) increased, it was necessary to diagnose the information service status of corporations and present improvement plans in agriculture. Therefore, we designed and conducted various surveys to understand the information service status of domestic agricultural company corporations.The research included ways to utilize information technology, establishing infrastructure related to information technology, current status of information technology application and impact on performance. Specifically, the main purpose of this study was to subdivide related corporations by industry and sales level and provide differentiated management implications for each sector. This is because the type of information service and information technology support that each corporation needs varies greatly depending on the industry and sales level. We provide customized management and policy proposals based on descriptive statistics and regression techniques.