• Title/Summary/Keyword: Smart farming

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A Study on the Types and Determinants of Young Farmers: Focusing on Young Farmers in Muan-gun, Jeollanam-do (청년농업인 유형화 및 결정요인 분석: 전남 무안군 청년농업인 중심으로)

  • Hyangmi Yi;Jongha Kim
    • Land and Housing Review
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    • v.15 no.2
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    • pp.107-124
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    • 2024
  • Based on Muan-gun, Jeollanam-do, this study explores how to mitigate the disappearance of rual areas. The study surveyed 95 young farmers in Muan-gun to assess their farming practices and the challenges they face. We further employ factor analysis and cluster analysis classify young farmers in Muan-gun, facilitating the identification of tailored policies or initiatives aimed at fostering and supporting young farmers. The results are summarized as follows. First, Muan County does not have any ordinances or original projects specifically designed to support young farmers. Second, the succession rate of farmland among young farmers in Muan County is 41.1%, which is comparable to the national rate of 43.7%. This indicates that approximately 40% of young farmers in Korea have inherited farmland, a critical foundation for agricultural activities. Third, despite accumulating farming experience, young farmers have not seen any improvement in local living conditions, and rather their difficulties have intensified. Fourth, this study conducted a factor analysis using 21 variables, resulting in the selection of seven common factors for cluster analysis. Consequently, young farmers in Muan County were categorized into three groups. The multinomial logit analysis revealed that the typology of young farmers is influenced by indicators such as cultivated area, farming experience, demand for smart farms, farm income, and farming type (rice cultivation or other). Therefore, to attract young farmers and prevent the decline of rural areas, policy efforts should focus on minimizing entry barriers to farming infrastructure, such as access to farmland, and improving local settlement conditions.

Utilization of Smart Farms in Open-field Agriculture Based on Digital Twin (디지털 트윈 기반 노지스마트팜 활용방안)

  • Kim, Sukgu
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2023.04a
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    • pp.7-7
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    • 2023
  • Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

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A Study on the Characteristic Analysis of the Pest Control Drones Using Smart Operating Mode (스마트운영모드를 활용한 방제드론 특성분석에 관한 연구)

  • Lim, Jin-Taek
    • Journal of Convergence for Information Technology
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    • v.9 no.10
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    • pp.108-113
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    • 2019
  • In relation to $4^{th}$ industrial revolution, it is required to build a smart agricultural system using the pest control drones, which are emerging fast these days as a role to support pest control work of farmers and improve aging issues in farming. However, the absence of accurate criteria on management of the pest control drones and the effect of pesticide application is leading to damage to crops by pesticides. The extreme shortage of analysis of management of the pest control drones and relevant studies, and big differences in pest control efficiency depending on the operation skills of controllers are the biggest reasons for the damage. Therefore, this paper suggests a basic study on agricultural pest control drone operation system buildup to make out working schedules and calculate the dosage of pesticide by understanding the features of the pest control drones properly based on the control using smart operating mode.

Analysis of Agricultural Tractor Transmission using Actual Farm Workload (실부하 적용을 통한 농용 트랙터 변속기 해석)

  • Kim, Jeong-Gil;Park, Jin-Sun;Choi, Kyu-Jeong;Lee, Dong-Keun;Shin, Min-Seok;Oh, Joo-Young;Nam, Ju-Seok
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.19 no.11
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    • pp.42-48
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    • 2020
  • The agricultural tractor is a multi-purpose vehicle, which is frequently used in the agricultural field. It must be highly reliable in terms of human safety. Design and analysis of agricultural tractors must be performed using actual agricultural workload to maintain high reliability. Additionally, the frequency with which various components and systems are used must also be taken into consideration. In this study, a tractor is built to measure its workload in the actual field. Further, the measured load was analyzed for various farming tasks. The range of ratios of consumed power to engine power was measured to be 42.6%-87.2%, 75.1%-97%, 26.5%-59.2% for a plow, rotary, and harvest tasks, respectively. The results were fed into a transmission simulation model to analyze the strength and life of the transmission components. We conclude that a more reliable product can be constructed by incorporating the transmission analyses using the actual load.

Design and Implementation of Produce Farming Field-Oriented Smart Pest Information Retrieval System based on Mobile for u-Farm (u-Farm을 위한 모바일 기반의 농작물 재배 현장 중심형 스마트 병해충 정보검색 시스템 설계 및 구현)

  • Kang, Ju-Hee;Jung, Se-Hoon;Nor, Sun-Sik;So, Won-Ho;Sim, Chun-Bo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.10 no.10
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    • pp.1145-1156
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    • 2015
  • There is a shortage of mobile application systems readily applicable to the field of crop cultivation in relation to diseases and insect pests directly connected to the quality of crops. Most of system have been devoted to diseases and insect pests that would offer full predictions and basic information about diseases and insect pests currently. But for lack of the instant diagnostic functions seriously and the field of crop cultivation, we design and implement a crop cultivation field-oriented smart diseases and insect pests information retrieval system based on mobile for u-Farm. The proposed system had such advantages as providing information about diseases and insect pests in the field of crop cultivation and allowing the users to check the information with their smart-phones real-time based on the Lucene, a search library useful for the specialized analysis of images, and JSON data structure. And it was designed based on object-oriented modeling to increase its expandability and reusability. It was capable of search based on such image characteristic information as colors as well as the meta-information of crops and meta-information-based texts. The system was full of great merits including the implementation of u-Farm, the real-time check, and management of crop yields and diseases and insect pests by both the farmers and cultivation field managers.

The ICT convergence agriculture automated machines designed for smart agriculture (스마트 농업을 위한 ICT 융합형 농업 자동화 기계 설계)

  • Kim, Byung-Chul
    • Journal of Digital Convergence
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    • v.14 no.2
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    • pp.141-148
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    • 2016
  • Agricultural machines can be viewed as a very important factor to reduce the workforce and reduce production costs as well as keep up with now days trend caused Labor shortages and the workforce reduction by aging in rural. The latest agricultural machinery has developed into a major agricultural industry to apply and integrate the telecommunication, next-generation batteries, semiconductors, wireless communications, content and high-tech display industry technology with a wide range of applications. In this study, to apply the information and communication technologies on agricultural planters relied on a mechanical method, we designed a quick and sophisticated ICT convergence planters that enable to monitor.

Implementation of an Environmental Monitoring System based on LoRa for Smart Field Irrigation (노지 관수를 위한 로라 기반 환경 모니터링 시스템 구현)

  • Kim, Byungsoon
    • Journal of Internet Computing and Services
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    • v.20 no.1
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    • pp.11-16
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    • 2019
  • Wireless sensor network is important for precision farming to monitor the growth environment of crops in open field, but radio signals are susceptible to different types of interference such as weather and physical objects. This paper designs and implements an environmental monitoring and weather forecast acquisition systems for smart field irrigation based on LoRa(Long Range) and then applies it to a test bed. And we evaluate the network reliability in terms of packet transmission success rate by comparing its condition on two criteria; the existence of obstacle or rain. The results show that much rain falls can affect on packet loss in LoRa field networks with obstacles.

An Implementation of Feeding Time Detection System for Smart Fish Farm Using Deep Neural Network (심층신경망을 이용한 스마트 양식장용 사료 공급 시점 감지 시스템 구현)

  • Joo-Hyeon Jeon;Yoon-Ho Lee;Moon G. Joo
    • IEMEK Journal of Embedded Systems and Applications
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    • v.18 no.1
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    • pp.19-24
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    • 2023
  • In traditional fish farming way, the workers have to observe all of the pools every time and every day to feed at the right timing. This method causes tremendous stress on workers and wastes time. To solve this problem, we implemented an automatic detection system for feeding time using deep neural network. The detection system consists of two steps: classification of the presence or absence of feed and checking DO (Dissolved Oxygen) of the pool. For the classification, the pretrained ResNet18 model and transfer learning with custom dataset are used. DO is obtained from the DO sensor in the pool through HTTP in real time. For better accuracy, the next step, checking DO proceeds when the result of the classification is absence of feed several times in a row. DO is checked if it is higher than a DO reference value that is set by the workers. These actions are performed automatically in the UI programs developed with LabVIEW.

A Survey of The Status of R&D Using ICT and Artificial Intelligence in Agriculture (농업에서의 ICT와 인공지능을 활용한 연구 개발 현황 조사)

  • Seonho Khang
    • Journal of the Semiconductor & Display Technology
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    • v.22 no.1
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    • pp.104-112
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    • 2023
  • Agriculture plays an industrial and economic role, as well as an environmental and ecological conservation role, group harmony and the inheritance of traditional culture. However, no matter how advanced the industry is, the basic food necessary for human life can only be produced through the photosynthesis of plants with natural resources such as the sun, water, and air. The Food and Agriculture Organization of the United Nations (FAO) predicts that the world's population will increase by another 2 billion people by 2050, and it faces a myriad of complex and diverse factors to consider, including climate change, food security concerns, and global ecosystems and political factors. In particular, in order to solve problems such as increasing productivity and production of agricultural products, improving quality, and saving energy, it is difficult to solve them with traditional farming methods. Recently, with the wind of the 4th industrial revolution, ICT convergence technology and artificial intelligence have been rapidly developing in many fields, but it is also true that the application of new technologies is somewhat delayed due to the unique characteristics of agriculture. However, in recent years, as ICT and artificial intelligence utilization technologies have been developed and applied by many researchers, a revolution is also taking place in agriculture. This paper summarizes the current state of research so far in four categories of agriculture, namely crop cultivation environment management, soil management, pest management, and irrigation management, and smart farm research data that has recently been actively developed around the world.

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Development and performance analysis of a crawler-based driving platform for upland farming (밭 농업용 무한궤도 기반 주행 플랫폼 개발 및 성능 분석)

  • Taek Jin Kim;Hyeon Ho Jeon;Md Abu Ayub Siddique;Jang Young Choi;Yong Joo Kim
    • Journal of Drive and Control
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    • v.20 no.4
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    • pp.100-106
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    • 2023
  • We developed a crawler-based driving platform that can perform harvesting, transportation, pest control, and rotary operation by equipping it with various implements, and analyzed its performance. This single platform was developed to perform as pepper harvester, peanut harvester, and transporter with a 46-kW engine. A simulation model was developed to study the specifications of the platform, and the accuracy was also analyzed. The absolute percentage error ranged from 0.2 to 5.9%, which made it possible to predict the platform performance using simulation model. In T-test, both torque and speed on field and asphalt showed a significant difference (1%). Driving torque required differed depending on the nature of the field, and the speeds also changed based on soil load. The developed platform has the advantage of being equipped with a variety of working tools, expected to be used to harvest root crops in the future.