• 드라이브 ㆍ 컨트롤
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• 제19권4호
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• pp.36-45
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• 2022

The aim of this study was to verify an E-driving system of a 44 kW-class electric tractor using agricultural workload data. Workload data were acquired during field test (plow tillage, rotary tillage, loader operation, field driving, asphalt driving) using a conventional tractor with a load measurement system. These workload data were converted to data of a 44 kW-class tractor based on the load factor of the engine. These data were used to verify the design of the E-driving system of an electric tractor. High-load operations such as plow tillage, rotary tillage, and loader operation could be performed at stage L and stage M. High-speed operation (asphalt driving) could be effectively performed at stage H using a rated rotational speed of the motor. As a result, the E-driving system of the electric tractor was possible to perform all major agricultural operations according to gear stages of range shift. Based on results of this research, we plan to develop an electric tractor equipped with an E-driving system and conduct research on actual vehicle verification in the future.

• 스마트미디어저널
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• 제1권1호
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• pp.42-47
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• 2012

IT 기술의 발전은, 우리사회의 다양한 산업 분야에 적용 되어 우리의 삶을 보다 효율적이고 생산적으로 바꾸고 있다. 농업IT는 이러한 IT기술을 농업에 적용하여 작물의 생산량과 품질을 향상시키며, 소비자로 하여금 믿을 수 있는 생산, 유통 정보를 제공하는 기술이다. 오늘날 RFID/USN의 등장은 농산물과 연관된 생장, 환경 정보의 수집을 가능하게 하고 각종 환경센서 등을 통해 수집된 디지털 정보는 누적, 분석 등을 통해 이상기후 예측, 병해충 예찰, 작물의 생산성 향상 및 균일 생산 보장 등을 위해 활용될 수 있을 것으로 기대된다. 본 연구에서는 이러한 RFID/USN 기술을 기반으로 저전력 센서네트워크와 미들웨어, 생장관리 플랫폼을 통해 모바일 환경에서 재배 환경 정보의 지속적 모니터링 및 각종 생장 데이터의 수집 및 전송, 각종 작업정보의 교환이 가능하게 함으로써 재배자에게 보다 효율적으로 생장환경을 관리할 수 있는 시스템을 제안한다.

• 한국정보통신학회논문지
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• 제19권7호
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• pp.1705-1710
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• 2015

근래에 ICT 기술을 농업에 적용시켜 효율성과 생산성을 제고시키는 기술인 스마트농업에 대한 연구개발이 활발히 이루어지고 있다. 그러나 아직 국제적으로 공인된 국제 표준이 구축되지 않아 외산 장비 도입과 해외 진출시 많은 어려움이 있는 상황이다. 이러한 필요에 의해 국제 표준화가 ITU-T SG13에서 국내 전문가들에 의해 추진되고 있다. 본 논문에서는 서비스 적용례를 기술할 수 있는 시나리오를 기반으로 하여 스마트농업 서비스들을 제안하며, 제안된 서비스 구성을 반영시킨 문서는 ITU-T Y.2238 권고안으로 승인되었다.

• 농업과학연구
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• 제47권4호
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• pp.1135-1145
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• 2020

The purpose of this study was to compare and analyze the emissions of SOx and NH3 for a 78 kW class agricultural tractor during agricultural operations. A real-time monitoring system was constructed for measuring the load data. The field test was conducted during plow and rotary tillage. The working conditions were selected with the transmission gears in M3 Low and M2 High for the plow tillage and L3 High and L3 Low for the rotary tillage. The engine torque and fuel consumption were measured using controller area network (CAN) communication, and the emissions of SOx and NH3 were calculated based on the fuel consumption. As a result of the field tests, the engine torque was higher for the plow tillage than for the rotary tillage. As the gear stage was increased, the engine torque became higher. The emissions of SOx and NH3 were higher for the plow tillage than for the rotary tillage because the fuel consumption increased. Moreover, the emissions of SOx and NH3 tended to be more distributed for the rotary tillage than for the plow tillage. To develop an emission factor for agricultural machinery, it is important to measure reliable emission data during agricultural operations. In a future study, we will collect various emission data using a portable emission measurement system during agricultural operations.

• 한국농공학회논문집
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• 제65권5호
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• pp.69-80
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• 2023

Carbon neutrality in agriculture can be derived from systematic GHG reduction policies based on quantitative environmental impact analysis of GHG-emitting activities. This study is to explore how to advance the calculation of carbon emissions from agricultural activities to the detailed spatial level to a spatial Tier 3 level (Tier 2.5 level), methodologically beyond the Tier 2 approach. To estimate the GHG emissions beyond the Tier 2.5 level by region for detailed spatial units, we constructed available activity data on carbon emission impact factors such as rice cultivation, agricultural land use, and livestock. We also built and verified detailed data on emission activities at the field level through field surveys. The GHG emissions were estimated by applying the latest national emission factors and regional emission factors according to the IPCC 2019 GL based on the field-level activity data. This study has significance that it explored ways to build activity data and calculate GHG emissions through statistical data and field surveys based on parcels, one of the smallest spatial units for regional carbon reduction strategies. It is expected that by utilizing the activity data surveyed for each field and the emission factor considering the activity characteristics, it will be possible to improve the accuracy of GHG emission calculation and quantitatively evaluate the effect of applying reduction policies.

• 대한원격탐사학회지
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• 제40권1호
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• pp.45-56
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• 2024

Faced with aging populations, declining resources, and limited agricultural productivity, rural areas in South Korea require innovative solutions. This study investigated the potential of drone-based vegetation indices (VIs) to analyze soybean growth patterns in open-field smart agriculture in Goesan-gun, Chungbuk Province, South Korea. We monitored multi-seasonal normalized difference vegetation index (NDVI) and the normalized difference red edge (NDRE) data for three soybean lots with different irrigation methods (subsurface drainage, conventional, subsurface drip irrigation) using drone remote sensing. Combining NDVI (photosynthetically active biomass, PAB) and NDRE (chlorophyll) offered a comprehensive analysis of soybean growth, capturing both overall health and stress responses. Our analysis revealed distinct growth patterns for each lot. LotA(subsurface drainage) displayed early vigor and efficient resource utilization (peaking at NDVI 0.971 and NDRE 0.686), likely due to the drainage system. Lot B (conventional cultivation) showed slower growth and potential limitations (peaking at NDVI 0.963 and NDRE 0.681), suggesting resource constraints or stress. Lot C (subsurface drip irrigation) exhibited rapid initial growth but faced later resource limitations(peaking at NDVI 0.970 and NDRE 0.695). By monitoring NDVI and NDRE variations, farmers can gain valuable insights to optimize resource allocation (reducing costs and environmental impact), improve crop yield and quality (maximizing yield potential), and address rural challenges in South Korea. This study demonstrates the promise of drone-based VIs for revitalizing open-field agriculture, boosting farm income, and attracting young talent, ultimately contributing to a more sustainable and prosperous future for rural communities. Further research integrating additional data and investigating physiological mechanisms can lead to even more effective management strategies and a deeper understanding of VI variations for optimized crop performance.

• International Journal of Internet, Broadcasting and Communication
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• 제15권2호
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• pp.144-156
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• 2023

Smart agriculture is a rapidly growing field that seeks to optimize crop yields and reduce risk through the use of advanced technology. A key challenge in this field is the need to create a comprehensive smart farm system that can effectively monitor and control the growth environment of crops, particularly when cultivating new varieties. This is where fuzzy theory comes in, enabling the collection and analysis of external environmental factors to generate a rule-based system that considers the specific needs of each crop variety. By doing so, the system can easily set the optimal growth environment, reducing trial and error and the user's risk burden. This is in contrast to existing systems where parameters need to be changed for each breed and various factors considered. Additionally, the type of house used affects the environmental control factors for crops, making it necessary to adapt the system accordingly. While developing such a framework requires a significant investment of labour and time, the benefits are numerous and can lead to increased productivity and profitability in the field of smart agriculture. We developed an AI platform for optimal control of facility houses by integrating data from mushroom crops and environmental factors, and analysing the correlation between optimal control conditions and yield. Our experiments demonstrated significant performance improvement compared to the existing system.

• 농업과학연구
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• 제50권4호
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• pp.617-628
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• 2023

This study aimed to evaluate the engine load factor (LF) of a 90 kW agricultural combine harvester. The combine harvester used in this study is equipped with an electronic engine, and real-time engine data (torque and speed) was collected through a controller area network. The speed of the combine harvester during harvesting operation was divided into three levels (4, 5, and 6 km/h) for the representative operation speed range of 4 to 6 km/h. The LF was calculated using the engine load data measured in real time during harvesting. A weight was applied to the LF for each condition based on a survey of the usage. Results of the field test showed that the LF was 0.53, 0.64, and 0.87 at working speeds of 4, 5, and 6 km/h, respectively. The highest engine load factor was recorded at 6 km/h. Finally, based on the weight for the usage applied, the integrated engine LF was analyzed to be 0.69, which is approximately 144% higher than the currently applied LF of 0.48. A study on LF analysis for the entire work cycle, including idling and driving of the combine harvester, will be addressed in a future study.

• International journal of advanced smart convergence
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• 제8권4호
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• pp.16-25
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• 2019

The Internet of things (IOT) is remodeling the agribusiness empowering the agriculturists through the extensive range of strategies, for example, accuracy as well as practical farming to deal with challenges in the field. The paper aims making use of evolving technology i.e. IoT and smart agriculture using automation. The objective of this research paper to present tools and best practices for understanding the role of information and communication technologies in agriculture sector, motivate and make the illiterate farmers to understand the best insights given by the big data analytics using machine learning. The methodology used in this system can monitor the humidity, moisture level and can even detect motions. According to the data received from all the sensors the water pump, cutter and sprayer get automatically activated or deactivated. we investigate a remote monitoring system using Wi-Fi. These nodes send data wirelessly to a central server, which collects the data, stores it and will allow it to be analyzed then displayed as needed and can also be sent to the client mobile.

• 한국농림기상학회지
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• 제20권1호
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• pp.18-33
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• 2018

기후스마트농업의 관점에서 무논점파 농법의 경쟁력을 평가하기 위하여 플럭스 타워(HPK)를 설치, 에디 공분산 방법으로 이산화탄소, 메탄 그리고 에너지의 교환량을 지속적으로 관측하고 있다. 본 통신문에서는 HPK 관측지에 대한 소개와 관측 자료의 처리과정 및 품질 관리에 대하여 문서화 하였다. KoFlux 표준화 방법에 따른 10단계 자료 처리 및 품질 관리과정을 거쳤으며, 이 과정에서 HPK 관측지의 자료 사용자들이 알아야 할 중요한 보정 단계를 이해하기 쉽도록 각 방법에 대한 개념과 일반적인 예를 들어 설명하였다. 자료 처리 과정에서 생성된 모든 자료들을 정리하여 데이터 서버에 저장하였으며, 모든 처리 과정을 거친 최종 자료를 사용하여 HPK 관측지에서 2016년 생장기간 동안 관측된 주 요소들에 대해 간략히 정량화 하였다.