• 대한원격탐사학회지
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• 제40권3호
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• pp.275-284
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• 2024

농업 분야에서 농작물의 생장 변화와 수분량 파악은 매우 중요하다. 본 연구에서는 수분에 민감하게 반응하는 단파적외(Short Wavelength Infrared, SWIR) 센서를 드론에 탑재하여 콩의 생장과 수분량 변화를 관찰하였다. 콩의 생장이 활발해질 때 수분량이 증가하는 현상을 확인했으며, 관수량의 차이에 따라 식생지수와 수분지수가 다르게 감소하는 것을 확인했다. 이는 습해로 인해 콩의 생장 둔화와 수분량 감소가 나타났음을 시사한다. 본 연구는 농작물의 생산성 저하와 습해 피해 감소를 위해 콩의 생장 단계별 식생지수와 수분지수를 세밀하게 모니터링할 것을 제안한다. 이로써 습해 뿐만 아니라 가뭄과 같은 수분 변화가 농작물 생장에 미치는 악영향을 조기에 탐지하여 예방할 수 있을 것으로 판단한다. 드론 기반 SWIR 센서를 통한 수분 스트레스의 조기 진단 가능성을 제시함으로써 대규모 농작물 관리의 효율성을 높이고 수확량을 증가시켜 농업 생산에 기여할 것으로 기대된다.

• 반도체디스플레이기술학회지
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• 제22권1호
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• pp.1-5
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• 2023

Most of the production process is performed in a cleanroom in the case of facilities that produce semiconductor chips or display panels. Therefore, environmental management of cleanrooms is very important for product yield and quality control. Among them, airborne particles are a representative management item enough to be the standard for the actual cleanroom rating, and it is a part of the Fab or Facility monitoring system, and the sequential particle monitoring system is mainly used. However, this method has a problem in that measurement efficiency decreases as the length of the sampling tube increases. In addition, a statistically significant test of deterioration in efficiency has rarely been performed. Therefore, in this study, the statistically significant test between the number of particles measured by InSitu and the number of particles measured for each sampling tube ends(Remote). Through this, the efficiency degradation problem of the sequential particle monitoring system was confirmed by a statistical method.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.390-393
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• 2008

We analyzed the landuse change, quantify the area covered by majors food crops (Paddy, Wheat, Barely, Maize, Millet and Potato) and their productivity trends in Terai, Nepal from 1987 to 2006. We used series of area covered by each single crop and production data published by Government of Nepal, Central Bureau of Statistics and Ministry of Agriculture and Cooperatives. Our results indicated that the agriculture land has increased by about 47% while forest has decreased by 32% between 1964 and 2001 in Terai. Whilst the total cropped area has increased by 19% between 1987 and 2006. The highest incremental change has observed in Potato by 234% followed by Wheat 31%, Maize 20% and Paddy 12% and so on. However, data revealed with very low crops productivity and it showed less than half of its potential except in Potato. The average yield of food crops /hectare /year during last 20 year has found only 3.094 metric tons. Only Potato has gained high average yield by 10.34 metric tons. While others crops yielded entirely low. 3 periods moving average depicted that the productivity trend of Barely and Millet has stagnant while others crops showed slightly up and down and increasing steadily over time. Further study is needed to comprehend the linkage of food productivity in the present food supply to demand and food security system in Terai, Nepal.

• 산업경영시스템학회지
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• 제45권4호
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• pp.180-186
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• 2022

Agrophotovoltaic (APV) system is an integrated system producing crops as well as solar energy. Because crop production underneath Photovoltaic (PV) modules requires delicate management of crops, smart farming equipment such as real-time remote monitoring sensors (e.g., soil moisture sensors) and micro-climate monitoring sensors (e.g., thermometers and irradiance sensors) is installed in the APV system. This study aims at introducing a decision support system (DSS) for smart farming in an APV system. The proposed DSS is devised to provide a mobile application service, satellite image processing, real-time data monitoring, and performance estimation. Particularly, the real-time monitoring data is used as an input of the DSS system for performance estimation of an APV system in terms of production yields of crops and monetary benefit so that a data-driven function is implemented in the proposed system. The proposed DSS is validated with field data collected from an actual APV system at the Jeollanamdo Agricultural Research and Extension Services in South Korea. As a result, farmers and engineers enable to efficiently produce solar energy without causing harmful impact on regular crop production underneath PV modules. In addition, the proposed system will contribute to enhancement of the smart farming technology in the field of agriculture.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.1010-1013
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• 2009

농촌의 청년들이 대도시로 대거 진출하여 농촌에 남아 생산에 종사하는 인력의 대부분이 노년층이 되어 온 것이 오래전부터의 일이다. 이들 노년층에게 있어서 가축에게 사료를 주는 일보다는 오히려 축사의 배설물을 치우는 일이 힘겨운 일이기 때문에 무엇보다 이부분의 자동화가 필요하다고 본다. 따라서 우리는 가축들의 폐사를 줄이기 위하여 축사의 배설물을 청소할 수 있고 혹한기와 혹서기 때 급격한 온도변화에 빠르게 대응할 수 있는 자동화시스템을 개발해 왔다. 시스템의 동작 환경을 원격지에서 모니터링 하기위하여 CCD 카메라를 이용하여 실시간으로 감시할 수 있는 시스템도 제안하였다. 본 논문에서는 이동 중에 축사 자동화 시스템을 제어할 수 있도록 PDA를 이용한 원격제어 시스템을 제안하였다. 제안 시스템은 사용자가 이동하고 있는 동안에 PDA 화면을 이용하여 제어 및 모니터링이 가능하도록 구현하였다. 또한 화재 및 외부로부터의 침입이 있을 경우 경고를 보내 도난을 방지하기 위한 보안시스템도 추가하였으며 도난 및 화재 등 비상시에 상황을 실시간으로 모바일을 이용하여 문자전송을 받을 수 있도록 구현하였다.

• 한국환경복원기술학회지
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• 제2권1호
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• pp.29-37
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• 1999

Land cover classification is an essential basic information in natural environment management; however, land cover classification studies in Korea have not yet been proceeded to a sufficient level. At the present, only a limited number of the precedent studies that only cover definite city area has been conducted. Furthermore, there is almost no research conducted on the land cover classification schemes that could accurately classify the Korea's land cover conditions. This study primarily focuses on the land cover classification scheme which carries the most urgent priority in order to classify and to map out the Korean land cover conditions. In order to develop the most suitable land cover classification scheme, many foreign land cover classification cases and projects that are being carried out were reviewed in depth. The land cover classification scheme this study proposes comprises 3 levels : The first level consists of 7 different classes; the second level consists of 22 different classes; and the third level is made up of 50 classes. The land cover classification map will serve many important roles in natural environment management, such as the conjecture of natural habitats and estimation of oxygen production or carbon dioxide absorption capability of a forest. In water pollution modelling, the land cover classification data can be used to estimate and locate non-point sources of water pollution. If applied to a watershed, modelling it will allow to estimate the total amount of pollution from non-point sources of pollution in the water shed. The land cover classification data will also be good as a barometer data that determines defusion of air pollutants in air pollution modelling.

• Journal of Biosystems Engineering
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• 제39권2호
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• pp.134-141
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• 2014

Purposes: This study was to validate the Robotic Smart Work System that can provides better working conditions and high productivity in unstructured environments like bio-industry, based on a tele-operation system for fruit harvesting with low cost 3-D positioning system on the laboratory level. Methods: For the Robotic Smart Work System for fruit harvesting and cultivation management in agriculture, a vision based tele-operating system and 3-D position information are key elements. This study proposed Robotic Smart Farming, an agricultural version of Robotic Smart Work System, and validated a 3-D position information system with a low cost omni camera and a laser marker system in the lab environment in order to get a vision based tele-operating system and 3-D position information. Results: The tasks like harvesting of the fixed target and cultivation management were accomplished even if there was a short time delay (30 ms ~ 100 ms). Although automatic conveyor works requiring accurate timing and positioning yield high productivity, the tele-operation with user's intuition will be more efficient in unstructured environments which require target selection and judgment. Conclusions: This system increased work efficiency and stability by considering ancillary intelligence as well as user's experience and knowhow. In addition, senior and female workers will operate the system easily because it can reduce labor and minimized user fatigue.

• Asian-Australasian Journal of Animal Sciences
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• 제18권6호
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• pp.780-786
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• 2005

This study presents a non-video, non-invasive, automatic, on-site monitoring system the system employs ultrasonic transducers to detect behavior in sows before, during and after parturition. An ultrasonic transmitting/receiving (T/R) circuit of 40 kHz was mounted above a conventional parturition bed. The T/R units use ultrasonic time-of-flight (TOF) ranging technology to measure the height of the confined sows at eight predetermined locations. From this data, three momentary postures of the sow are determined, characterized as standing-posture (SP), lateral-lying-posture (LLP) and sitting posture (STP). By examining the frequencies of position switch Stand-Up-Sequence (SUS) between standing-posture (SP), lateral-lying-posture (LLP) and sitting-posture (STP) rate can be determined for the duration of the sow' confinement. Three experimental pureblooded Landrace sows undergoing normal gestation were monitored for the duration of confinement. In agreement with common observation, the sows exhibited increased restlessness as parturition approached. Analysis of the data collected in our study showed a distinct peak in Stand-Up-Sequence (SUS, i.e. the transition from lying laterally to standing up ) and sitting-posture (STP) rate approximately 12 h prior to parturition, the observed peak being 5 to 10 times higher than observed on any other measurement day. It is concluded that the presented methodology is a robust, low-cost, lowlabor method for the continuous remote monitoring of sows and similar large animals for parturition and other behavior. It is suggested that the system could be applied to automatic prediction of sow parturition, with automatic notification of remote management personnel so human attendance at birth could reduce rates of sow and piglet mortality. The results of this study provide a good basis for enhancing automation and reducing costs in large-scale sow husbandry and have applications in the testing of various large mammals for the effects of medications, diets, genetic modifications and environmental factors.

• 대한원격탐사학회지
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• 제40권1호
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• pp.57-69
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• 2024

Crop classification plays a vitalrole in monitoring agricultural landscapes and enhancing food production. In this study, we explore the effectiveness of Long Short-Term Memory (LSTM) models for crop classification, focusing on distinguishing between apple and rice crops. The aim wasto overcome the challenges associatedwith finding phenology-based classification thresholds by utilizing LSTM to capture the entire Normalized Difference Vegetation Index (NDVI)trend. Our methodology involvestraining the LSTM model using a reference site and applying it to three separate three test sites. Firstly, we generated 25 NDVI imagesfrom the Sentinel-2A data. Aftersegmenting study areas, we calculated the mean NDVI values for each segment. For the reference area, employed a training approach utilizing the NDVI trend line. This trend line served as the basis for training our crop classification model. Following the training phase, we applied the trained model to three separate test sites. The results demonstrated a high overall accuracy of 0.92 and a kappa coefficient of 0.85 for the reference site. The overall accuracies for the test sites were also favorable, ranging from 0.88 to 0.92, indicating successful classification outcomes. We also found that certain phenological metrics can be less effective in crop classification therefore limitations of relying solely on phenological map thresholds and emphasizes the challenges in detecting phenology in real-time, particularly in the early stages of crops. Our study demonstrates the potential of LSTM models in crop classification tasks, showcasing their ability to capture temporal dependencies and analyze timeseriesremote sensing data.While limitations exist in capturing specific phenological events, the integration of alternative approaches holds promise for enhancing classification accuracy. By leveraging advanced techniques and considering the specific challenges of agricultural landscapes, we can continue to refine crop classification models and support agricultural management practices.

• 한국토양비료학회지
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• 제45권5호
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• pp.749-759
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• 2012

본 연구는 벼 생산력을 예측할 수 있는 지상원격 측정센서 및 반사율지표를 선발하고, 이삭거름 질소 시비량 추천을 위한 원격탐사 최적 검정시기를 평가하며. 효율적 원격탐사 지표에 의한 이삭거름 질소 시비량 추천모델을 추정하고자 2010년에 포장시험이 수행되었다. 질소 시비량은 작물별 시비처방기준 (NIAST, 2006) 에 의해 결정하였고, 질소 시비수준은 기준 질소 시비량의 0%, 70%, 100% 및 130%의 4수준으로 하였으며, 밑거름으로 70%, 이삭거름으로 30%로 하여 분시하였다. 벼는 추청과 주남을 공시품종으로 하여 사양토에 5월 22일에 이앙하였고, 10월 6일에 수확하였다. 지상원격탐사 반사율 지표는 Crop Circle-amber와 red, GreenSeeker-green과 red를 이용해 7월 5일부터 8월 23일까지 7회에 걸쳐 측정하였다. 지상원격탐사 센서의 헤드와 작물 캐노피와의 형성 각도에 따라 센서가 탐지하는 식생의 밀도가 달라질 수 있다는 가정 하에 센서 헤드와 작물 캐노피의 측정 각도를 $45^{\circ}$, $70^{\circ}$ 및 $90^{\circ}$ 각도로 조정하여 반사율 지표를 측정하였다. 지상원격탐사 센서로 측정된 반사율 지표는 $70^{\circ}$ 및 $90^{\circ}$ 각도로 측정하였을 때 전반적으로 양호한 상관을 보여주었고, 생육 중반기와 수확기의 벼 지상부 건물중과 유의성 있는 상관을 보였다. 결정적 생육시기 (critical season)인 52일째와 59일째 측정된 반사율 지표는 벼의 지상부 건물중, 질소 흡수량과 밀접한 상관을 보여주었으며, 특히 이앙 후 59일째 측정한 NDVI가 고도로 밀접한 관계가 있음을 보여주었다. 이러한 결과로 추청벼는 59일째 GreenSeeker $70^{\circ}$ 각도 rNDVI가, 주남벼는 59일째 Crop Circle $45^{\circ}$ 각도 rNDVI 및 GreenSeeker $70^{\circ}$ gNDVI가 최종 수확기 벼의 지상부 건물중 및 질소 흡수량을 추정하고, 이들 지표는 충족지수로 평가하여 질소시비수준을 예측하고 이삭거름 질소시비추천모델로 활용할 수 있을 것으로 생각되었다.