• 한국멀티미디어학회논문지
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• 제25권2호
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• pp.297-310
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• 2022

Road facilities such as CCTV poles have potential risk of collision accidents with a car. A collision detection algorithm installed in the facility allows the collision accident to be known remotely. Most collision detection algorithms are operated by simply focusing on whether a collision have occurred, because these methods are used to measure only acceleration data from a 3-axis sensor to detect collision. However, it is difficult to detect other detailed information such as malfunction of the sensor, collision direction and collision strength, because it is not known without witness the accident. Therefore, we proposed enhanced detection algorithm to get the collision direction, and the collision strength from the tilt of the facility after accident using a 9-axis sensor in this paper. In order to confirm the performance of the algorithm, an accuracy evaluation experiment was conducted according to the data measurement cycle and the invocation cycle to an detection algorithm. As a result, the proposed enhanced algorithm confirmed 100% accuracy for 50 weak collisions and 50 strong collisions at the 9-axis data measurement cycle of 10ms and the invocation cycle of 1,000ms. In conclusion, the algorithm proposed is expected to provide more reliable and detailed information than existing algorithm.

• International Journal of Internet, Broadcasting and Communication
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• 제11권4호
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• pp.71-75
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• 2019

Sleep apnea is a disease that causes various complications, and the polysomnography is expensive and difficult to measure. The purpose of this study is to develop an unrestricted wearable monitoring system so that patients can be examined in a familiar environment. We used a method to detect sleep apnea events and to determine sleep satisfaction by non-constrained method using SpO2 measurement sensor and 3-axis acceleration sensor. Heart rate and SpO2 were measured at the finger using max30100. After acquiring the SpO2 data of the user in real time, the apnea measurement algorithm was used to transmit the number of apnea events of the user to the mobile phone using Bluetooth (HC-06) on the wrist. Using the three-axis acceleration sensor (mpu6050) attached to the upper body, the number of times of tossing and turning during sleep was measured. Based on this data, this algorithm evaluates the patient's tossing and turning during sleep and transmits the data to the mobile phone via Bluetooth. The power source used 9 volts battery to operate Arduino UNO and sensors for portability and stability, and the data received from each sensor can be used to check the various degree between sleep apnea and sleep tossing and turning on the mobile phone. Through thisstudy, we have developed a wearable sleep apnea measurement system that can be easily used at home for the problem of low sleep efficiency of sleep apnea patients.

• Journal of Biosystems Engineering
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• 제40권1호
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• pp.28-34
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• 2015

Purpose: This study aimed to install an RTK-GPS (Real Time Kinematic-Global Positioning System) and IMU (Inertial Measurement Unit) on a tractor used in a farm to measure positions, pasture topography, posture angles, and vibration accelerations, translate the information into maps using the GIS, analyze the characteristics of grass harvesting work, and establish new technologies and construction standards for pasture infrastructure improvement based on the analyzed data. Method: Tractor's roll, pitch, and yaw angles and vibration accelerations along the three axes during grass harvesting were measured and a GIS map prepared from the data. A VRS/RTK-GPS (MS750, Trimble, USA) tractor position measuring system and an IMU (JCS-7401A, JAE, JAPAN) tractor vibration acceleration measuring systems were mounted on top of a tractor and below the operator's seat to obtain acceleration in the direction of progression, transverse acceleration, and vertical acceleration at 10Hz. In addition, information on regions with bad workability was obtained from an operator performing grass harvesting and compared with information on changes in tractor posture angles and vibration acceleration. Results: Roll and pitch angles based on the y-axis, the direction of forward movements of tractor coordinate systems, changed by at least $9-13^{\circ}$ and $8-11^{\circ}$ respectively, leading to changes in working postures in the central and northern parts of the pasture that were designated as regions with bad workability during grass harvesting. These changes were larger than those in other regions. The synthesized vectors of the vibration accelerations along the y-axis, the x-axis (transverse direction), and the z-axis (vertical direction) were higher in the central and northwestern parts of the pasture at 3.0-4.5 m/s2 compared with other regions. Conclusions: The GIS map developed using information on posture angles and vibration accelerations by position in the pasture is considered sufficiently utilizable as data for selection of construction locations for pasture infrastructure improvement.

• 한국공간구조학회논문집
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• 제16권1호
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• pp.85-94
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• 2016

In this study, an acceleration sensor that has optical fibers to measure the inclination and acceleration of a structure through contradictory changes in two-component FBG sensors was examined. The proposed method was to ensure precise measurement through the unification of the deformation rate sensor and the angular displacement sensor. A high sensitivity three-axis accelerometer was designed and prepared using this method. To verify the accuracy of the accelerometer, the change in wavelength according to temperature and tension was tested. Then, the change in wavelength of the prepared accelerometer according to the sensor angle, and that of the sensor according to the change in ambient temperature were measured. According to the test results on the FBG-based vibration sensor that was developed using a high-speed vibrator, the range in measurement was 0.7 g or more, wavelength sensitivity, 2150 pm/g or more, and the change in wavelength change, $9.5pm/^{\circ}C$.

• 전기학회논문지
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• 제65권10호
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• pp.1746-1754
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• 2016

In this paper, we provide a development and evaluation method for an archery posture analyzing system, using an inertial sensor. The system was developed using LabVIEW2014 by National Instruments and evaluated using the DTW algorithm. To convert the voltage value of the inertial sensor into a physical value, a coordinate transformation matrix bias was applied. To evaluate the similarity of movement in archery shooting, the DTW distance was calculated and similarity was confirmed based on simple mechanical movement, the same person's shooting movement, shooting movement with another person, and the noise signal. The average similarity comparison results were as follows: simple mechanical movement was 17.05%, the same person's shooting movement was 26.48%, shooting movement with another person was 62.8%, and the noise signal was 328.5%; a smaller value indicates a higher level of similarity. We confirmed the possibility of analyzing the archery posture using 3-axis acceleration of the inertial sensor. We inferred that the proposed method might be important means for assessing shooting skills, evaluation of archer's progress, and finding talented archers in advance.

• 전자공학회논문지
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• 제52권5호
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• pp.190-196
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• 2015

본 논문은 항법장치 위치보정을 위해 칼만필터를 적용한 GPS/INS융합의 다중보정방법을 제안한다. 연구에서는 관성항법장치를 구현하기 위해 9축 항법장치로 보정알고리즘을 적용하여 위치오차를 감소시킨 방법을 적용했다. 일반적으로 GPS/INS는 위치정보를 얻어낼 수 있지만 위치정보를 구하는 과정에서 오차 또한 더불어 커지게 되기에 이를 보정하기 위한 강인한 오차 보정 알고리즘이 필요하다. 본 논문에서는 9축 관성센서(mpu-9150)의 외란에 대한 강인성 향상을 위해 가속도계 보정 알고리즘을 사용하여 tilt보정을 수행했으며, 제어 대상체의 정확한 방위를 파악할 수 있도록 Yaw각 재정의 알고리즘을 적용하였다. 최종적으로 GPS/INS와 칼만 필터를 함께 결합한 통합시스템을 구현하였다.

• 디지털콘텐츠학회 논문지
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• 제19권9호
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• pp.1779-1785
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• 2018

본 연구에서는 사물인터넷 기술을 이용하는 스마트 웨어러블 기기의 상황인식 기능을 향상시키기 위하여 센서부의 이벤트 데이터에 대한 오차 보정 방안을 제안하였다. 스마트 기기를 통한 상황인식에서 기기의 특성상 필수적인 상황 정보 센싱을 함에 있어서 오차가 불가피하게 발생하고, 이는 예측 성능을 저하시키는 요인이 된다. 이러한 문제를 해결하기 위하여 본 연구에서는 칼만필터의 오류보정 알고리즘을 적용하여 스마트기기의 3축 가속도 센서에서 입수되는 신호 값을 보정하였다. 결과적으로 시계열 데이터를 이루는 3축 가속도 센서가 감지하여 보고하는 데이터에 대한 처리 과정에서 발생하는 오차를 칼만필터를 통하여 효과적으로 제거할 수 있었다. 이 연구가 차후 개발되어질 실시간 상황인지 시스템의 성능을 향상시켜 줄 수 있을 것이라 기대한다.

• 인터넷정보학회논문지
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• 제18권3호
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• pp.11-17
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• 2017

To the elderly, sudden falls are one of the most frightening accidents. If an accident occurs, a prompt action has to be taken to deal with the situation. Recently, there have been a number of attempts to detect sudden falls using acceleration sensors embedded in the mobile devices, such as smart phones and wrist-bands. However, using the sensor readings only, the detection rate of the falls is around 65%. Ordinary daily activities such as running or jumping could not be well distinguished from the falls. In this paper, we describe our attempts on improving the fall-detection rate. We implemented a wrist-band fall detection module, using a three-axis acceleration sensor. With the pattern matching on the fall signal-strength frequency spectrum, in addition to the conventional signal strength measurement, we could improve the detection rate by 9% point. Furthermore, by applying two wrist-bands in the experiment, we could further improve the detection rate to 82%.

• 제어로봇시스템학회논문지
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• 제21권9호
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• pp.818-826
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• 2015

This paper presents a novel methodology for estimating vehicle ego-motion, i.e. tri-axis linear velocities and angular velocities by using stereo vision sensor and 2G1Y sensor (longitudinal acceleration, lateral acceleration, and yaw rate). The estimated ego-motion information can be utilized to predict future ego-path and improve the accuracy of 3D coordinate of obstacle by compensating for disturbance from vehicle movement representatively for collision avoidance system. For the purpose of incorporating vehicle dynamic characteristics into ego-motion estimation, the state evolution model of Kalman filter has been augmented with lateral vehicle dynamics and the vanishing point estimation has been also taken into account because the optical flow radiates from a vanishing point which might be varied due to vehicle pitch motion. Experimental results based on real-world data have shown the effectiveness of the proposed methodology in view of accuracy.

• 한국정보통신학회논문지
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• 제24권9호
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• pp.1224-1230
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• 2020

스마트폰의 보급 이후 웨어러블 디바이스에 대한 관심이 높아지고 다양화되면서 사용자들의 생활에 밀접하게 연관되고 있으며, 개인화된 서비스를 제공하기 위한 방법으로 사용되고 있다. 본 논문에서는 스마트폰에 내장된 3축 가속도 센서와 3축 자이로 센서의 정보를 합성곱 신경망에 적용하여 사용자의 행동을 검출하는 방법을 제안한다. 인간의 행동은 동작의 크기와 범위에 따라서 동작을 구성하는 신호 데이터의 지속시간을 포함한 시작 시점과 끝나는 시점이 다르다. 이로 인해 합성곱 신경망에 그대로 적용하면 행동 인식 정확도에 대한 성능상의 문제가 있다. 따라서 센서 데이터를 시간의 구간에 따라 분할된 특징을 학습하는 시분할 특징 융합 합성곱 신경망(TDFFCNN: Time-Division Feature Fusion Convolutional Neural Network)을 제안하였다.