• Journal of Biosystems Engineering
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• 제33권6호
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• pp.423-429
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• 2008

This study was performed to investigate the effects of inertial navigation system (INS) / global positioning system (GPS) sensor fusion for agricultural vehicle navigation. An extended Kalman filter algorithm was adopted for INS/GPS sensor fusion in an integrated mode, and the vehicle dynamic model was used instead of the navigation state error model. The INS/GPS system was consisted of a low-cost gyroscope, an odometer and a GPS receiver, and its performance was tested through computer simulations. When measurement noises of GPS receiver were 10, 1.0, 0.5, and 0.2 m ($1{\sigma}$), RMS position and heading errors of INS/GPS system at 5 m/s straight path were remarkably reduced with 10%, 35%, 40%, and 60% of those obtained from the GPS receiver, respectively. The decrease of position and heading errors by using INS/GPS rather than stand-alone GPS can provide more stable steering of agricultural equipments. Therefore, the low-cost INS/GPS system using the extended Kalman filter algorithm may enable the self-autonomous navigation to meet required performance like stable steering or more less position errors even in slow-speed operation.

• 동력기계공학회지
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• 제13권1호
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• pp.65-71
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• 2009

To address the need for new intelligent sensing, this paper introduces nano sensors made of carbon nanotube (CNT) composites and presents their preliminary experiments. Having smart material properties such as piezoresistivity, chemical and bio selectivity, the nano composite can be used as smart electrodes of the nano sensors. The nano composite sensor can detect structural deterioration, chemical contamination and bio signal by means of its impedance measurement (resistance and capacitance). For a structural application, the change of impedance shows specific patterns depending on the structural deterioration and this characteristic is available for an in-situ multi-functional sensor, which can simultaneously detect multi symptoms of the structure. This study is anticipated to develop a new nano sensor detecting multiple symptoms in structural, chemical and bio applications with simple electric circuits.

• International journal of advanced smart convergence
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• 제13권3호
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• pp.101-108
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• 2024

This paper addresses the implementation of an on-device AI-based metal detection system using a Magneto-Impedance Sensor. Performing calculations on the AI device itself is essential, especially for unmanned aerial vehicles such as drones, where communication capabilities may be limited. Consequently, a system capable of analyzing data directly on the device is required. We propose a lightweight gated recurrent unit (GRU) model that can be operated on a drone. Additionally, we have implemented a real-time detection system on a CPU embedded system. The signals obtained from the Magneto-Impedance Sensor are processed in real-time by a Raspberry Pi 4 Model B. During the experiment, the drone flew freely at an altitude ranging from 1 to 10 meters in an open area where metal objects were placed. A total of 20,000,000 sequences of experimental data were acquired, with the data split into training, validation, and test sets in an 8:1:1 ratio. The results of the experiment demonstrated an accuracy of 94.5% and an inference time of 9.8 milliseconds. This study indicates that the proposed system is potentially applicable to unmanned metal detection drones.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.391-392
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• 2006

In x-ray imaging system, twokinds of noises are involved. First, the charge generated from the radiation interaction with the detector during exposure is modeled by Poisson process. Second, the signal is then added by readout electronics noise, which is modeled by Gaussian distribution. In this paper, we applied Wiener filter and Wavelet to remove noise from medical X-ray image, the result shows that wavelet yield better segmentation results than the wiener filter.

• 한국컴퓨터정보학회논문지
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• 제16권1호
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• pp.117-124
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• 2011

본 논문은 생체 센서 시스템(bio-physical sensor system)을 이용하여 홈 네트워크 시스템을 구성하고, 생체 신호가 전달되도록 생체 신호 원격용 네트워크를 구현하였다. 측정 시스템의 구성조건은 시각(Vision), 체성감각(Somatosensory), 전정기관(Vestibular), 중추신경계통(CNS)의 변위점에서 평가하고, 맥박(Heart Rate), 체온(Temperature), 체중(Weight)을 기본 측정항목에 사용하였다. 주파수 변동에 따른 0.01 단위로 측정하여 평균값을 가지고 기준치에 비교하여 설정환경을 구성하고 측정값을 결정하였다. 생체 신호는 신체의 균형조절기능인 신경생리학적 감각처리 및 운동 출력기전으로 시각, 체성감각, 전정기관, 중추신경계통, 체질량지수(BMI)의 신체적 감각 기관의 수용체들 간의 운동에 대한 균형과 자세를 통한 기준으로 정상적인 균형 조절 상태와 균형의 크기 형태로 구분하고, 건강의 상태를 확인하도록 의미를 부여하였다. 본 연구의 결과로 제안한 홈 네트워크를 통해 헬스 센터 및 건강관리 중앙 시스템에 단말기를 통하여 전송됨으로 전문가을 통한 건강 관리시스템이 진행되는 결과를 얻을 수 있고, 다양한 신체적 파라메타를 통한 원격네트워크 모니터링 기능의 관리시스템이 형성 될 것으로 추론 할 수 있다.

• 반도체디스플레이기술학회지
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• 제20권3호
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• pp.103-107
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• 2021

In this paper, a capacitive water level sensor for boilers was developed. In order to accurately monitor the water level in a high-temperature boiler that generates a lot of precipitates, the occurrence of precipitates on the surface of the water level sensor should be small, and a sensor capable of measuring even if the sensor surface is somewhat contaminated is required. The capacitive water level sensor has a structure in which one of the two electrodes is insulated with Teflon coating, and the stainless steel package of the water level sensor is brought into contact with the water tank so that the entire water tank becomes another electrode of the water level sensor. A C-V converter that converts the capacitance change of the capacitive water level sensor into a voltage change was developed and integrated with the water level sensor to minimize noise. The performance of the developed capacitive water level sensor was evaluated through measurement.

• 한국통신학회논문지
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• 제38A권6호
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• pp.528-534
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• 2013

센서 네트워크에서 기본적으로 고려되어야 하는 것은 센서 노드의 에너지 소모 문제이다. 이를 해결하기 위해 많은 연구들이 진행되어 왔지만 에너지 소모 문제와 더불어 트레이드오프 관계를 갖는 지연 문제도 간과할 수 없는 부분이다. 본 논문은 생체시스템을 모방하여 무선 센서망에서 에너지의 소모와 지연시간을 줄이기 위한 BISA(Bio-inspired Scheduling Algorithm)를 제안한다. BISA는 에너지 효율성이 높은 라우팅 경로를 탐색하고 다중채널을 이용하여 데이터 전송의 경로를 다중화하여 데이터 전송을 위한 에너지 소모와 지연시간을 최소화한다. 모의실험을 통해 제안한 방식이 효율적으로 에너지를 소모함과 동시에 요구지연시간을 보장함을 확인한다.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.II
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• pp.333-343
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• 2000

An automatic guidance system for combine was designed to harvest paddy rice by following a predetermined path. The automatic guidance system consisted of DGPS to locate position of combine, a gyro sensor system to measure heading angle, ultrasonic sensors to detect obstacles, a hydraulic system, microcomputer as a controller, and I/O interface system. Hydraulic cylinders and valves were installed to control movement of the combine. The heading angle and the position of the combine, and ultrasonic measurements from edge were used as the inputs of the controller. The operating position of hydraulic cylinder was determined as output of the controller. The automatic guidance system was evaluated at the 45-m straight path by changing the posture of the combine. The average RMS errors were 14.0 cm without offset and 15.0 cm with 1-m offset. The DGPS provided accurate position information within the limited error to guide the combine in the field. The results showed that the automatic guidance system could guide the combine autonomously in the paddy field when the posture of the combine was changed.

• Journal of Biosystems Engineering
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• 제43권2호
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• pp.138-147
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• 2018

Purpose: A narrowband hyperspectral imaging sensor of high-dimensional spectral bands is advantageous for identifying the reflectance by selecting the significant spectral bands for predicting crop yield over the broadband multispectral imaging sensor for each wavelength range of the crop canopy. The images acquired by each imaging sensor were used to develop the models for predicting the Chinese cabbage yield. Methods: The models for predicting the Chinese cabbage (Brassica campestris L.) yield, with multispectral images based on unmanned aerial vehicle (UAV), were developed by simple linear regression (SLR) using vegetation indices, and forward stepwise multiple linear regression (MLR) using four spectral bands. The model with hyperspectral images based on the ground were developed using forward stepwise MLR from the significant spectral bands selected by dimension reduction methods based on a partial least squares regression (PLSR) model of high precision and accuracy. Results: The SLR model by the multispectral image cannot predict the yield well because of its low sensitivity in high fresh weight. Despite improved sensitivity in high fresh weight of the MLR model, its precision and accuracy was unsuitable for predicting the yield as its $R^2$ is 0.697, root-mean-square error (RMSE) is 1170 g/plant, relative error (RE) is 67.1%. When selecting the significant spectral bands for predicting the yield using hyperspectral images, the MLR model using four spectral bands show high precision and accuracy, with 0.891 for $R^2$, 616 g/plant for the RMSE, and 35.3% for the RE. Conclusions: Little difference was observed in the precision and accuracy of the PLSR model of 0.896 for $R^2$, 576.7 g/plant for the RMSE, and 33.1% for the RE, compared with the MLR model. If the multispectral imaging sensor composed of the significant spectral bands is produced, the crop yield of a wide area can be predicted using a UAV.

• 생물환경조절학회지
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• 제1권1호
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• pp.61-71
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• 1992

This study is performed to develop an automatic irrigation control of system for effective water management in greenhouse. The automatic irrigation control system is composed of an IR-RED optical sensor in tensiometer and an One-chip micro controller. The following results are obtained : 1. A practical IR-RED optical sensor in tensiometer, which shows the starting point of irrigation, was developed. 2. The automatic irrigation system with the optical sensor and One-chip micro controller was developed and also designed to be able to combine with the control system for temperature, curtain opening, etc. 3. A multiple irrigation control system for several greenhouses were suggested. 4. The results of the system test with the driving program for automatic water management were excellent.