• 제목/요약/키워드: Precision Farming

검색결과 92건 처리시간 0.023초

DEVELOPMENT OF A MACHINE VISION SYSTEM FOR WEED CONTROL USING PRECISION CHEMICAL APPLICATION

  • Lee, Won-Suk;David C. Slaughter;D.Ken Giles
    • 한국농업기계학회:학술대회논문집
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    • 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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    • pp.802-811
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    • 1996
  • Farmers need alternatives for weed control due to the desire to reduce chemicals used in farming. However, conventional mechanical cultivation cannot selectively remove weeds located in the seedline between crop plants and there are no selective heribicides for some crop/weed situations. Since hand labor is costly , an automated weed control system could be feasible. A robotic weed control system can also reduce or eliminate the need for chemicals. Currently no such system exists for removing weeds located in the seedline between crop plants. The goal of this project is to build a real-time , machine vision weed control system that can detect crop and weed locations. remove weeds and thin crop plants. In order to accomplish this objective , a real-time robotic system was developed to identify and locate outdoor plants using machine vision technology, pattern recognition techniques, knowledge-based decision theory, and robotics. The prototype weed control system is composed f a real-time computer vision system, a uniform illumination device, and a precision chemical application system. The prototype system is mounted on the UC Davis Robotic Cultivator , which finds the center of the seedline of crop plants. Field tests showed that the robotic spraying system correctly targeted simulated weeds (metal coins of 2.54 cm diameter) with an average error of 0.78 cm and the standard deviation of 0.62cm.

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자동차 부품용 알루미늄 압출재의 프레스 성형기술 (Press Forming of Extruded Aluminum Profile for Automotive Parts)

  • 최영;박준홍;강면규;오개희;박상우;여홍태
    • 한국정밀공학회지
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    • 제23권5호
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    • pp.51-58
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    • 2006
  • The necessities for heightening fuel efficiency as well as lightweight design, lead to an increase of the use of aluminum alloys in the automobile industry. Extruded aluminum profile channels are used widely for the design of frame parts as lightweight assemblies, especially if a high stiffness is needed. While many applications can be realized with forming of hollow square-sectioned extruded profiles such as a stretch bending and a hydro-forming, some applications demand the use of a press bending which can be hardly found in the previous study. In this study, by introducing the use of a press bending into car sub-frames, the demands for higher accuracy as well as higher flexible method than the conventional methods will be satisfied. With respect to the design of sub-frames, the process planning was performed from the shape of a sub-frame product. The designed processes were analyzed by the commercial FEM code, DEFORM-3D. Forming dies for the each process were designed and prototypes of sub-frames were manufactured by the verified farming process. In addition, some of the important features of design parameters in the press bending were reviewed.

불가사리 채집 로봇 플랫폼의 개념설계 및 분석 (Starfish Capture Robotic Platform: Conceptual Design and Analysis)

  • 진상록;이석우;김종원;서태원
    • 한국정밀공학회지
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    • 제29권9호
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    • pp.978-985
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    • 2012
  • Starfish are a critical problem for fishermen since they eat every farming product including shellfish. The number of starfish is increasing dramatically because they have no natural enemy underwater. We consider the concept of capturing starfish using a semi-autonomous robot. A new underwater robot design to capture starfish is proposed using cooperation between humans and the robot. A requirements list for the robot is developed and two conceptual designs are proposed. Each robot is designed as a modular platform. The kinematic and dynamic performance of each robot is analyzed and compared. This study is a starting point for developing a starfish capture robot and designing underwater robots for other applications. In the near future, a prototype will be assembled and tested in a marine environment.

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

  • 김병순
    • 인터넷정보학회논문지
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    • 제20권1호
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    • pp.11-16
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    • 2019
  • 노지 정밀농업에서 작물의 생육환경 측정을 위한 무선 센서 네트워크 기술이 중요시되고 있지만 무선 신호는 다양한 전파장애 요인들에 의해 통신 장애가 발생할 수 있다. 이 논문은 노지 관수를 위해 로라 기반 환경 모니터링과 일기예보 정보수집 시스템을 설계 및 구현하고 이를 테스트베드에 적용하였다. 그리고 장애물이 있는 환경과 장애물이 없는 환경, 비 오는 날과 비 오지 않은 날 각각에 대하여 사설 로라 네트워크의 패킷 손실률을 비교 분석하였으며, 장애물이 있는 로라 네트워크는 강우량이 많은 날은 패킷손실에 민감함을 알 수 있었다.

Deep Learning for Weeds' Growth Point Detection based on U-Net

  • Arsa, Dewa Made Sri;Lee, Jonghoon;Won, Okjae;Kim, Hyongsuk
    • 스마트미디어저널
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    • 제11권7호
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    • pp.94-103
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    • 2022
  • Weeds bring disadvantages to crops since they can damage them, and a clean treatment with less pollution and contamination should be developed. Artificial intelligence gives new hope to agriculture to achieve smart farming. This study delivers an automated weeds growth point detection using deep learning. This study proposes a combination of semantic graphics for generating data annotation and U-Net with pre-trained deep learning as a backbone for locating the growth point of the weeds on the given field scene. The dataset was collected from an actual field. We measured the intersection over union, f1-score, precision, and recall to evaluate our method. Moreover, Mobilenet V2 was chosen as the backbone and compared with Resnet 34. The results showed that the proposed method was accurate enough to detect the growth point and handle the brightness variation. The best performance was achieved by Mobilenet V2 as a backbone with IoU 96.81%, precision 97.77%, recall 98.97%, and f1-score 97.30%.

Techniques for Yield Prediction from Corn Aerial Images - A Neural Network Approach -

  • Zhang, Q.;Panigrahi, S.;Panda, S.S.;Borhan, Md.S.
    • Agricultural and Biosystems Engineering
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    • 제3권1호
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    • pp.18-28
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    • 2002
  • Neural network based models were developed and evaluated for predicting corn yield from aerial images based on 1998 and 1994 image data. The model used images in multi-spectral bands such as R, G, B, and IR (Red, Green, Blue and Infrared). The inputs to the neural network consisted of mean and standard deviation of multispectral bands of the aerial images. Performances of several neural network architectures using back-propagation with momentum were compared. The maximum yield prediction accuracy obtained was 97.81%. The BPNN model prediction accuracy could be enhanced by using more number of observations to the model, other data transformation techniques, or by performing optical calibration of the aerial image.

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정밀농업을 위한 작물 생육정보 획득시스템 개발 (Development of Crop Growth Information Acquisition System for Precision Farming)

  • 성제훈;정선옥;홍석영;이동현
    • 한국농업기계학회:학술대회논문집
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    • 한국농업기계학회 1999년도 하계 학술대회 논문집
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    • pp.165-170
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    • 1999
  • 정밀농업의 기본개념은, 작물 생육상태를 포함한 포장정보가 위치마다 다르므로 포장정보에 따라 위치별로 적합한 농자재 투입과 생육관리를 통하여 수확량은 극대화하면서도 불필요한 농자재의 투입을 최소화해서 농자재 낭비와 환경오염을 줄이는 것이다. 이러한 정밀농업을 위해서는 무엇보다도 다양한 위치별 포장정보를 정확하고 빠르게 수집하는 기술이 선행되어야 한다 포장정보는 일반적으로 비교적 장기간에 걸쳐 변화가 일어나는 정보와 단기간에 변화가 일어나는 정보 두 가지로 나누어 볼 수 있다. 장기간에 걸쳐 변화가 일어나는 정보는 포장의 크기 및 형태, 진입로, 수로, 토성, 토양 유기물 함량 등이고, 단기간에 변화가 일어나는 정보는 병충해, 성장중인 작물의 건강상태 등을 예로 들 수 있다. 이러한 정보 중 단기간에 변화가 일어나는 정보는 빠른 시간 내에 적절한 처리를 해 주어야만 수확량 및 수확된 곡물의 질에 미치는 나쁜 영향을 최소화할 수 있으며, 실시간으로 분석이 되어야만 작업기를 이용한 정밀한 포장관리가 가능하다. (중략)

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On-line Real Time Soil Sensor

  • Shibusawa, S.
    • Agricultural and Biosystems Engineering
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    • 제4권1호
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    • pp.28-33
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    • 2003
  • Achievements in the real-time soil spectro-photometer are: an improved soil penetrator to ensure a uniform soil surface under high speed conditions, real-time collecting of underground soil reflectance, getting underground soil color images, use of a RTK-GPS, and all units are arranged for compactness. With the soil spectrophotometer, field experiments were conducted in a 0.5 ha paddy field. With the original reflectance, averaging and multiple scatter correction, Kubelka-Munk (KM) transformation as soil absorption, its 1st and 2nd derivatives were calculated. When the spectra was highly correlated with the soil parameters, stepwise regression analysis was conducted. Results include the best prediction models for moisture, soil organic matter (SOM), nitrate nitrogen (NO$_3$-N), pH and electric conductivity (EC), and soil maps obtained by block kriging analysis.

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스마트 농업을 위한 생산량 예측 방법 (Yield Forecasting Method for Smart Farming)

  • 이준구;문애경
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2015년도 추계학술대회
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    • pp.619-622
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    • 2015
  • 최근 심각한 기후변화로 인하여 농산물 생산성 및 농산물 가격의 변동성이 커지고 있으며, 이러한 문제를 해결하기 위하여 농산물의 생산량을 예측하는 방법이 연구되고 있다. 본 논문에서는 선형 방정식을 이용하여 생산 단수, 생산 면적, 기후 요소를 예측하였으며, 기후 요소의 가중치 합을 이용하여 보정된 생산 단수와 생산 면적을 곱하여 생산량을 계산하였다. 실험에서 예측한 생산량은 실제 생산량과 비교하여 약 90% 이상의 예측율을 보였다.

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정밀농업 구현을 위한 농업용 GIS 구축 (Construction of Agricultural GIS for Realizing Precision Farming)

  • 조성인;장영창;여운영
    • 한국농업기계학회:학술대회논문집
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    • 한국농업기계학회 2002년도 동계 학술대회 논문집
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    • pp.507-513
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    • 2002
  • 본 연구에서는 정밀농업 구현을 위해 필수 불가결의 요소인 데이터베이스 구축의 필요성에 착안하여 공간 및 속성 데이터 구축 알고리즘의 설계와 데이터베이스를 구성하는 테이블의 스키마 설계를 통해 공간 및 비공간 데이터를 구축하고 구축된 데이터베이스와의 통신을 통해 농작업 기계의 위치에 따른 토양 속성값을 추출해 내는 과정을 보임으로써 의사결정 지원시스템으로서의 기능을 시뮬레이션을 통해 제시하였다. 연구에 사용된 공간 및 비공간 데이터 구축에 있어서의 수작업은 작업자로 하여금 노동 소모적인 작업을 요구하므로 차후의 연구에 있어 보다 자동화되고 개선된 알고리즘의 개발이 요구된다. 또한 구축되어야 하는 경작지의 규모가 커지고 비공간 데이터의 양이 많아지게 되면 데이터베이스내의 검색 성능 향상에 대한 고찰 또한 병행되어야 할 것으로 판단된다.

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