• 한국초지조사료학회지
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• 제40권4호
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• pp.196-202
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• 2020

본 연구는 동계사료작물의 무인기기반 생육모니터링을 위하여 호밀, 총체보리, IRG를 대상으로 다중분광영상으로 건물수량을 예측하기 위한 최적식생지수를 테스트하였다. 2019년 2월부터 4월까지 나주의 실경작지에서 무인기 다중분광카메라로 분광영상을 수집하여 4종류의 식생지수(Normalized Difference Vegetation Index; NDVI, Green Normalized Difference Vegetation Index; GNDVI, Normalized Green Red Difference Index; NGRDI and Normalized Difference Red Edge Index; NDREI)를 산출하고 지상에서 건물수량을 조사하여 식생지수와 건물수량의 상관관계를 조사하였다. 호밀, 총체보리, IRG에 대하여 건물수량과 NDVI의 상관관계(R2)는 0.91~0.92, GNDVI는 0.92~0.94, NGRDI는 0.71~0.85, NDREI는 0.84~0.91로 GNDVI가 가장 효과적이었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.479-484
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• 1999

Rice crop has relatively short growing season during the summer in Korea and, therefore, it is often difficult to acquire cloud-free imagery on time. This study was attempt to define the temporal characteristics of radar backscattering observed from satellite L-band SAR data on different growing stages of rice crop. Six scenes of multi-temporal JERS SAR data were obtained from the transplanting season to the harvesting month of October. Six layers of multi-temporal SAR data were registered on a common geographic coordinate system. Using topographic maps, field collected data, and Landsat TM data, several sample rice fields were delineated from the imagery and their relative radar backscatters were calculated by using a set of reference targets. The temporal pattern of radar backscattering was very distinctive by the growing stage of rice crop. It was also separable between two types of rice fields having different cultivation practices. Considering the temporal characteristics of radar backscattering observed from the study, it is obvious that a certain date of the growing season can be more effective to delineate the exact area of the cultivated rice crop field.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2006년도 한국약용작물학회 공동춘계학술발표회
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• pp.40-54
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• 2006

It's not easy to detect the high quality and functional compounds for control quality of food materials. The electronic nose was an instrument, which comprised of an array of electronic chemical sensors with partial specificity and an appropriate pattern recognition system, capable of recognizing simple or complex odors. It can conduct fast analysis and provide simple and straightforward results and is best suited for quality control and process monitoring in the field of functional foods. Numbers of applications of an electronic nose in the functional food industry include discrimination of habitats for medicinal food materials, monitoring storage process, lipid oxidation, and quality control of food and/or processing with principal component analysis, neural network analysis and the electronic nose based on GC-SAW sensor. The electronic nose would be possibly useful for a wide variety of quality control in the functional food and plant cultivation when correlating traditional analytical instrumental data with sensory evaluation results or electronic nose data.

• 한국정보전자통신기술학회논문지
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• 제16권4호
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• pp.210-219
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• 2023

농촌 인구의 감소와 고령화로 인한 노동력 부족, 비닐하우스 내의 악화된 환경과 위험에 따른 사망 사례가 발생하고 있다. 이에 따라, 비닐하우스에서의 작물 재배와 병해 검출을 자동화하여 인력 손실을 막는 시스템이 필요하다. 본 논문에서는 비닐하우스에서 작물의 병해를 검출하기 위해 객체 검출 기반의 모델을 활용한다. 또한, 클라우드에서 인공지능 모델의 환경을 구성하여 안정성을 확보한다. 제안하는 시스템은 비닐하우스 내에서 촬영한 영상을 데이터베이스에 저장하고, 클라우드에서 영상을 다운로드한 후 Yolo-v4를 기반으로 추론한 검출 결과를 JSON 파일로 생성한다. 이 파일을 분석하여 데이터베이스로 전송하여 저장한다. 실험 결과로 객체 검출을 통한 병해 감지는 비닐하우스와 같은 실제 환경에서 높은 성능을 나타냄을 확인할 수 있고 데이터베이스를 통하여 효율적인 모니터링이 가능함을 확인하였다.

• 한국농림기상학회지
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• 제3권1호
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• pp.37-43
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• 2001

Crop status monitoring and yield prediction at higher spatial resolution is a valuable tool in various decision making processes including agricultural policy making by the national and local governments. A prototype crop forecasting system was developed to project the size of rice crop across geographic areas nationwide, based on daily weather pattern. The system consists of crop models and the input data for 1,455 cultivation zone units (the smallest administrative unit of local government in South Korea called "Myun") making up the coterminous South Korea. CERES-rice, a rice crop growth simulation model, was tuned to have genetic characteristics pertinent to domestic cultivars. Daily maximum/minimum temperature, solar radiation, and precipitation surface on 1km by 1km grid spacing were prepared by a spatial interpolation of 63 point observations from the Korea Meteorological Administration network. Spatial mean weather data were derived for each Myun and transformed to the model input format. Soil characteristics and management information at each Myun were available from the Rural Development Administration. The system was applied to the forecasting of national rice production for the recent 3 years (1997 to 1999). The model was run with the past weather data as of September 15 each year, which is about a month earlier than the actual harvest date. Simulated yields of 1,455 Myuns were grouped into 162 counties by acreage-weighted summation to enable the validation, since the official production statistics from the Ministry of Agriculture and Forestry is on the county basis. Forecast yields were less sensitive to the changes in annual climate than the reported yields and there was a relatively weak correlation between the forecast and the reported yields. However, the projected size of rice crop at each county, which was obtained by multiplication of the mean yield with the acreage, was close to the reported production with the $r^2$ values higher than 0.97 in all three years.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2005년도 국제학술회의
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• pp.75-87
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• 2005

Remote sensing(RS)- and geographic information system(GIS)-based information management to measure and assess agri-environment schemes, and to quantify and map environment indicators for nature and land use, climate change, air, water and energy balance, waste and material flow is in high demand because it is very helpful in assisting decision making activities of farmers, government, researchers, and consumers. The versatility and ability of RS and GIS containing huge soil database to assess agricultural environment spatially and temporally at various spatial scales were investigated. Spectral and microwave observations were carried out to characterize crop variables and soil properties. Multiple sources RS data from ground sensors, airborne sensors, and also satellite sensors were collected and analyzed to extract features and land cover/use for soils, crops, and vegetation for support precision agriculture, soil/land suitability, soil property estimation, crop growth estimation, runoff potential estimation, irrigated and the estimation of flooded areas in paddy rice fields. RS and GIS play essential roles in a management and monitoring information system. Biosphere-atmosphere interection should also be further studied to improve synergistic modeling for environment and sustainability in agri-environment schemes.

• Journal of Biosystems Engineering
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• 제38권1호
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• pp.25-32
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• 2013

Purpose: The objective of this study is to develop a data middleware for u-IT convergence in agricultural environment monitoring, which can support non-standard data interfaces and solve the compatibility problems of heterogenous sensor networks. Methods: Six factors with three different interfaces were chosen as target data among the environmental monitoring factors for crop cultivation. PostgresSQL and PostGIS were used for database and the data middleware was implemented by Python programming language. Based on hierarchical model design and key-value type table design, the data middleware was developed. For evaluation, 2,000 records of each data access interface were prepared. Results: Their execution times of File I/O interface, SQL interface and HTTP interface were 0.00951 s/record, 0.01967 s/record and 0.0401 s/record respectively. And there was no data loss. Conclusions: The data middleware integrated three heterogenous sensor networks with different data access interfaces.

• 한국응용곤충학회지
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• 제52권4호
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• pp.341-348
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• 2013

비래해충인 멸강나방 성충의 발생을 실시간으로 예찰하기 위하여, 성페로몬 트랩에 원격감지장치를 설치한 트랩의 운용 효율성을 검정하였다. 원격감지트랩은 콘트랩 기반에 곤충의 유입을 광차단으로 감지하는 센서부, 신호전송부, 태양열기반의 전력공급부, 트랩 지지대, 웹페이지 기반의 자료수집부로 구성되었다. 연구과정에서 멸강나방 수컷 성충의 밤 시간대 포획의 일일주기성을 이용한 신호감지 시간대 축소, 신호발생 프로그램 조절, 1시간 간격의 전송간격, 신호전송 프로그램 변형 등을 통해 포획 나방수와 감지신호 발생 수의 격차를 줄여 최종적으로 신호 정확도를 92% 이상으로 개선하였다. 또한 실제 멸강나방 성충의 발생양상과 원격감지트랩에서의 신호 발생양상의 상관계수가 0.98이상으로 원격감지트랩에서의 신호 발생이 멸강나방 발생 양상을 정확하게 반영하는 것으로 나타났다. 2011~2012년 멸강나방은 연중 여러 번 발생되는 것이 관찰되었는데, 모두 짧은 기간 동안 발생되어 가파른 피크가 특징이었다.

• 한국멀티미디어학회논문지
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• 제19권11호
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• pp.1891-1899
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• 2016

Recently food problem and crop disaster have been increased continuously because of the meteorological changes. These cause rising cost for crops continuously and irregularly. Some researchers have studied straight structure of device for hydroponics and plant factory previously to solve a fundamental part of these problems. However, there are several problems such as limited crop cultivation space, providing irregular nutrients for crops, and lack of monitoring interfaces. For them, we propose an optimal growth and development crops management system using light source tracking and recirculation of nutrient solution method to supply nutrient continuously based on IoT. In order to evaluate the performance of our system, we compared and analyzed in terms of two viewpoints, the tracking analysis for natural light source measurement and the growth of crops through artificial light, LED, respectively. We confirmed that the higher the duty ratio of LED, the larger the crop's size, particularly. As well as, for about 1 month, we compared with the existing natural light growing environment and that of our system. It was confirmed that the size of the crops grown through our system is about three times larger than that of natural light natural crops.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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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.