Earticle

최근 대도시 핵심 교통수단인 도시철도의 대중화와 노후화에 따른 다양한 문제점이 발생되고 있다. 본 연구에서 는 이의 해결을 위해 스마트폰 내장형 가속도센서와 이를 활용한 애플리케이션을 사용하여 대구광역시 도시철도 1호선 전 구간에 대한 진동가속도를 측정하고 열차진동 특성을 평가하였다. 이를 위해 국내 철도차량 진동 측정 방법(KS R 9160)을 따라 주행 시 발생하는 3축 방향 가속도를 기반으로, 32개 역사 구간 및 방향 별 진동가속도 특성을 분석하였 다. 또한, 1997년 개통 당시 측정된 주요 구간 진동가속도와의 비교를 통해 열차 진동환경 변화에 따른 진동증폭 양상 을 모니터링하였다. 진동가속도 분석 결과, 20년에 걸친 철도시설 환경의 노후화에 따른 수평 및 수직 방향 진동가속도 증가 특성을 확인하였다. 본 연구의 결과는 추후 도시철도 승차감 평가와 주변 구조물에 대한 진동영향성 평가를 위한 주요한 자료로서의 가치가 있을 것으로 판단된다.

Recently, various problems have arisen due to the popularization and aging of urban railway transit, which is the key transportation of large cities. In this study, the vibrational accelerations for the Daegu Metropolitan City Urban Railway(Line 1) were measured and evaluated using the smartphone built–in acceleration sensor and the approved application. For this purpose, the three axes running accelerations were measured according to the domestic standard (KS R 9160), and the acceleration data along the 32 stations (3 directions) were analyzed and compared. In addition, the increasing of acceleration values caused by the change of vibrational environment was monitored along the main stations between the time in 1997 and 2017. It was found that there are considerable increase of lateral and vertical directional accelerations due to the aging of railway facility environment for the last 20 years. The results of this study have valuable means for evaluating the ride quality of urban railway and the vibration influence on surrounding structures.

본 논문에서는 실제 값과 같은 데이터의 불확실성과 유사성을 측정 할 수 있는 퍼지 엔트로피와 유사성 측정이 소개되고 있다. 퍼지 엔트로피와 유사성 측정의 디자인이 설명하고 입증했다. 획득 수단은 연산 프로세스에 적용되고 논의되었다. 이러한 의사 결정과 퍼지 게임 이론과 같은 데이터 정량화 결과의 연장도 논의되었다.

In this paper, fuzzy entropy and similarity measure to measure the uncertainty and similarity of data as real value were introduced. Design of fuzzy entropy and similarity measure were illustrated and proved. Obtained measures were applied to the calculating process and discussed. Extension of data quantification results such as decision making and fuzzy game theory were also discussed.

센서 네트워크에서는 데이터의 실시간 처리가 중요한 요소 중의 하나이다. 각 노드들이 감지한 데이터들은 정해진 시간 내에 전송 되어야만 필요한 시기에 정확한 처리가 가능하다. 따라서 노드들이 데이터를 정해진 시간 내에 제대로 전달하고 있는가를 점검하는 것은 매우 중요하다. 최근 리얼타임 임베디드 시스템이 점점 더 정확해져 서 신뢰성 있고 정교한 서비스를 제공할 수 있게 되었다. 임베디드 시스템의 본래의 복잡함 때문에 물리세계에서의 예측의 어려움과 안전한 설계의 어려움은 런타임에서 시스템 제약사항에 위배되는 것과 예상치 못한 상황을 야기시 키는 원인이 된다. 각 노드들이 감지한 데이터를 정해진 시간 내에 전달해야 필요한 시기에 적합한 처리가 가능하기 때문에 본 논문에서는 데이터 전송시간에 대한 모니터링을 통하여 센서 네트워크에 존재하는 노드들이 허용시간 범위 내에서 서버로 데이터를 전송하고 있는가를 확인하기 위한 데이터 전송시간 분석 시스템을 구현 하였다. 시스 템 구현을 위하여 데이터 전송시간 분석을 위한 절차를 제시했고, 제시한 절차에 따라 전송시간을 분석하기 위해 필요한 시간차 분석 방법, 데이터 송수신 시간 수집 방법 및 데이터 전송시간 계산 방법을 제시했다.

Real-time processing of sensor data network, is one of the important factors. Each node in the detected data are required to be transmitted within a certain time since the accurate processing is possible. Thus, the data nodes are successfully delivered within a specified time, it is very important to check whether the. Recently more and more accurate real-time embedded systems are reliable and haejyeoseo been able to provide sophisticated services. Because of the inherent complexity of embedded systems in the physical world and the difficulty of predicting the difficulty of a safe design constraints on the runtime violation of system as to cause unexpected causes. Each node data in time detected by the time required to be passed in the appropriate processing is possible because the data transfer time in this paper, the monitoring of the sensor network through a node are allowed to exist within the time range and transmits data to the server Analysis of the data transfer time for checking whether the system was implemented. Implementation of the data transmission time to the process for analyzing and presenting, according to the procedure suggested by the transit time required for analysis a time difference analysis method, a data collection method and a data transmission time and transmission time calculating method presented.

유비쿼터스 환경에서 최근 스마트 폰에서 증강현실(Augmented Reality) 서비스가 활발히 구현되고 있다. 본 논문에서는 아이폰에 탑재된 카메라와 가속도 센서를 이용한 모바일 증강현실 시스템을 개발하였다. 일반적으로 카메라만을 이용하는 경우, 가려짐이나 빠른 움직임으로 인해 마커를 검출하지 못하는 상황이 발생한다. 이를 해결하기 위해 마커가 가려지는 시점에서부터 아이폰에서 제공되는 가속도 출력값을 사용하여 일정 시간 동안의 카메라의 움직임을 해석함으로써 모바일 게임용 증강현실 어플리케이션을 제공하는 기술이 제안된다. 실험결과로부터 마커가 가려지는 경우에도 모바일 단말의 움직임을 효과적으로 해석함을 확인하였다.

Augmented Reality (AR) services on a smart phone have been developed actively in ubiquitous environment. This paper presents a novel mobile system using camera and accelerometer sensor built in iPhone. Using the camera sensing disables to deal with the case the marker for AR is occluded or the camera moves so fast. By using the output of the acceleration sensing in iPhone, the proposed method provides continuous AR application even though when the marker is undetected. The experimental results showed that we achieve a precise estimation of the device movement in AR application such as mobile game.

Currently, falling to industrial field workers is causing serious injuries. Therefore, many researchers are actively studying the fall by using acceleration sensor, gyro sensor, pressure sensor and image information.Also, as the spread of smartphones becomes common, techniques for determining the fall by using an acceleration sensor built in a smartphone are being studied. The proposed method has complexity due to fusion of various sensor data and it is still insufficient to develop practical application. Therefore, in this paper, we use acceleration sensor module built in smartphone to collect acceleration data, propose a simple falling algorithm based on accelerometer sensor data after normalization and preprocessing, and implement an Android based app.

인간은 잠을 자는 동안에 지친 몸과 마음을 회복한다. 밥을 먹는 것만큼이나 수면은 당연한 일이지만 잠을 자지 못해 병원을 찾는 사람들이 많다. 최근에 보급되는 거의 모든 스마트폰에는 가속도센서를 포함하여 다양한 센서 를 탑재함에 따라 U-헬스케어 서비스 분야에서 환자 또는 의료진에게 스마트폰 기반의 의료용 애플리케이션을 제공 하기 위한 많은 연구가 진행되고 있다. 본 논문에서는 가장 대중화된 스마트폰에 내장되어 있는 각종 센서들을 사용 하여 사용자의 행동을 인식하여 정상적인 수면흐름을 유도할 수 있도록 안드로이드 기반의 애플리케이션을 제공하는 목적이다.

Humans must restore tired bodies and minds during sleep. Sleep as much as eating a meal many people looking for a hospital can not sleep, but a matter of course. The smart phone is loaded in the most recent studies it has been conducted to provide a service to the patient or medical personnel Uhealthcare in the field of smart phone-based medical applications as with a variety of sensors, including an acceleration sensor. In this paper, the aim of providing an Android-based applications to use a variety of sensors incorporated in the popularity of smart phones to induce normal water flow to recognize the user's action.

Information technology and medical advances in technology transformed the paradigm of health. In the past, the focus had been on the treatment, but today the current focus is towards maintaining health. This is research project based on the outdoors, running, walking, biking, in contrast to indoor exercise (weight training) can be utilized in an area where research is lacking. This paper is based on a variety of indoor acceleration sensor movement get figures for the record. This sensor sends data obtained through the Web and market themselves through a suitable exercise program or from users through their Smartphone with purchased recommended programs. Through this research, may be able to have goal-oriented exact figures in the future.

In this paper, a motion recognition scheme using acceleration sensor of smart devices is proposed and is experimentally analyzed with a server. Sensor data of 3-axis acceleration of a smart device is collected and 2nd order Butterworth low pass filter (LPF) is applied to reduce noise. With the collected sensor data, the various motions such as falling, sitting, lying and walking are distinguished one another. Based on the fixed threshold by the probability approach, falling motion is especially distinguished from other motions as an indication of emergency situation. A server displays current states and alarm states. The proposed scheme is evaluated through experiments. The results of experiments show that the accuracy of motion recognition is more than 94% in all the motions. As for a falling recognition, the accuracy is 96%.

Estimation of walking direction is important for providing detailed information about an individual’s gait. This study proposes a method for estimating walking direction using a shoe-mounted acceleration sensor. Heel contact is determined from the negative peak of the acceleration magnitude, and foot inclination is calculated for estimating the horizontal acceleration. The stepping direction of each foot is calculated through principle component analysis along the horizontal acceleration. The walking direction is estimated by averaging consecutive left- and right-step directions. The proposed method was applied to out-door straight ground walking for 658 steps, and yielded a mean difference of 0.48° with a standard deviation of 1.98°.

In this paper, we propose algorithm for determining the static and dynamic posture using the acceleration sensor of smartphone. The measured acceleration values are then analyzed according to a preprocessing to the respective axis (X, Y, Z) and posture (standing, sitting, lying) presents static posture determination criterion. The proposed static posture determination condition is used for static posture determination and dynamic posture determination. The dynamic posture is determined by using regression linear equations. In addition, transition state can be grasped by SVM change in dynamic posture determination. Experimental results are presented using data and app. Experiments were performed using data collected from 10 adults.

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 this study, 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.

As GPS technology has been developed with other mobile communications, GPS function is essentially loaded on mobile devices including smartphone and tablet PC. Thus, users can exchange information based on the current location of the GPS through the application service such as path-finding and current velocity. However, since it is difficult to identify accurate means of transportation of a user, there is limitation on providing high-quality service and information. For instance, it causes unnecessary data consumption that providing unnecessary traffic information to a user walking or riding city rails.

A wireless body sensor system (WBSS) provides diverse healthcare services by attaching sensors to the arms, abdomen, and feet of a user and by swiftly obtaining the user’s movement and health-related information. In order to overcome the battery limitations of sensors and the variations in wireless channels in such WBSSs, much research is being conducted. This paper aims to propose a new packet transmission power control (TPC) mechanism that judges wireless channel conditions using acceleration values and inhibits packet transmission when the channel is unstable, thereby reducing energy consumption. The TPC mechanism proposed in this paper was able to save energy efficiently while not increasing the delay time much when the channel condition changed.

최근 스마트폰을 가지고 있는 사람이 증가하고 있는 추세이며 이에 대한 다양한 연구가 활발히 진행 중이다. 이러한 상황에서 센서기술과 스마트폰의 융합으로 다양한 기능을 제공한다. 본 논문에서 제안한 시스템은 컨트롤러에서 3축가속도센서를 통한 사용자의 움직임에 대한 가속도정보를 추출하며 이 가속도 정보를 블루투스를 통하여 스마트폰에 전송한다. 기존의 스마트폰에서 사용되던 터치입력이나 버튼입력방식이 아닌 동작에 따른 3축 가속도센서를 이용한 입력방식이므로 언제 어디서든 스마트폰을 직접 만지지 않아도 컨트롤이 가능하다. 또한 다양한 기능성 애플리케이션의 개발로 인하여 활용도가 매우 높다.

Recently, as the number of people using Smartphones increased, several researches has been launched basing it's subject on this issue. In this circumstance, the fusion of sensor technologies and Smartphone offers a variety of functions. The system introduced in the current paper uses a controller which extracts information about accelerating movements of an user. This information is then sent to the Smartphone through Bluetooth communication. The input method proposed in this paper differs from the existing methods such as touch typing or button input in Smartphones. It rather uses the 3-D acceleration sensor which enables users to control their Smartphone anywhere and anytime without directly touching the device. Furthermore, because it is developed for various applications, it can be applied in many different fields.

본 논문은 3축 가속도센서를 이용한 사고를 방지하기위한 시스템 설계에 관한 연구이다. 전원 공급단에 스위칭 파워 FET를 구성하였고, 전원 공급장치는 DC-DC, 레귤레이터, LDO를 설계하였다. 전원 문제를 한번에 해결하기 위해 2원화를 하였으며, 3축 가속도 센서를 설계하여 움직임 정보를 추출하여 안전하게 사고를 예방할 수 있도록 설계하였다. 마이크로프로세서는 I2C, UART 통신 포트를 통해 통신할 수 있도록 하였으며, J-LINK를 통해 디버깅 할 수 있도록 하였다. 가속도 센서 데이터 측정결과 30° 이상의 각도의 움직임을 감지했을 때 정상적으로 사고 방지를 위해 전원이 차단되는 것을 확인 할 수 있었다.

In this paper is a study on system design to prevent accidents using accelerometers. A switching power FET was configured at the power supply stage, and DC-DC converter, a regulator, and an LDO were designed for the power supply. In order to solve the power problem at once, it was divided into two parts, and a 3-axis accelerometer was designed to extract motion information to safely prevent accidents. Microprocessor enables communication through I2C and UART communication ports, and enables debugging through J-LINK. As a result of measuring the acceleration sensor data, it was confirmed that the power is normally cut off to prevent accidents when motion at an angle of 30 〫or more is detected.

In airborne gravimetry, there are two data streams. One is the specific force measured by an air/sea gravimeter or accelerometers, the other is kinematic acceleration measured by DGPS. And the difference of them provides the gravity disturbance information. To satisfy the requirement of most applications, an accuracy of 1mGal $(1mCal=10^{-5}m/s^{2})$ with a spatial resolution of 1km is the aim of current airborne gravimetry. There are two different methods to derive the kinematic acceleration. The generally used method is to differentiate the position twice, and the position can be calculated by commercial DGPS software. The main defect of this method is that integer ambiguities need to be fixed to get the precise position solution, but it's not a trivial thing for long base line. And to fix integer ambiguities, the noisier iono-free measurement is used. When differentiation is applied, noise is amplified and will influence the accuracy of acceleration. The other method is to get carrier phase acceleration by differentiate the carrier phase first, and then using the acceleration of GPS satellite to derive the vehicle acceleration. The main advantages include that fixing integer ambiguities is not needed anymore, position can be relaxed to about 10 meters, and smoother acceleration can be got since iono-free measurement is not needed. In some literatures, it's considered that the dynamic performance of the second method is inferior to that of the first. Through analysis, it is found that the performance degradation in dynamic environment results from the simplification of the GPS carrier phase observable model. And an iterative algorithm is presented to compensate the model error. Using a dynamic GPS data from an aeromagnetic survey, the importance of this compensation is showed at last.

In this paper, we deal with two bias compensation algorithms of acceleration sensor for measuring the galloping on power transmission line. Firstly, the block diagram of galloping measurement system is given and a galloping model is presented. Secondly, two compensation algorithms, a simple compensation and a period compensation, are proposed. A simple compensation algorithm use the drafts of velocity and distance at fixed periods, so it is useful for constant bias case. Next, a period compensation algorithm can compensate a periodic bias. This algorithm use the previous measured data and compensated data for constant period, where the period is obtained by FFT method. Lastly, the effectiveness of proposed algorithms is verified by comparing between two algorithms in simulation, and its characteristics and the bias error bound are shown, respectively.

In this paper, a device to analyze gait pattern was developed by using a 2-axis acceleration sensor attached to the foot. The 1st low-pass filter was adapted to limit the frequency band up to 5 Hz. An algorithm to detect the peak value exceeding the threshold voltage of an X-axis acceleration sensor and a Z-axis acceleration sensor was developed and normal and abnormal walking patterns were thus differentiated. Also, MCU and Bluetooth were combined to transfer the data to other MCUs to display on an LCD; the size of the device could then be reduced. The new algorithm and the device allowed the individual walking patterns to be easily measured at a low cost and with less restriction on activities compared to conventional multiple pressure sensors or motion camera system.

The amount of heat applied to the welding part by the movement of the welding torch has a predetermined standard per unit area, according to the base material and the welding method. When the heat input is large, the cooling rate is slowed and the ductility is increased; however, as the hardness is decreased, the welding part is easily deformed by the residual stress. Further, if the amount of heat input is small, the weld zone tends to separate due to the lack of welding. Therefore, for a constant amount of heat to be applied to the weld, it is essential to measure the real-time moving speed, direction, and angle of the torch during welding. In this paper, we propose welding and weaving speed estimation system using an acceleration sensor based on the support vector machine (SVM). To measure the welding and weaving speeds, we analyze the obtained signal from the acceleration sensor in the frequency domain, based on the fast Fourier transform (FFT), and derive the feature vector. Based on this, we apply the SVM to improve the accuracy of low speed measurement by classifying the characteristics of the measurement signal according to the speed change. To verify the validity, we analyze the accuracy and error of the proposed algorithm according to the change in welding and weaving speed. The simulation result shows that the proposed method achieves an average positioning accuracy of 93.36% and a maximum positioning error of 0.3834 m.

In this paper, we propose a new framework to control VR(Virtual reality) contents in real time using user's mouth-wind and acceleration sensor of mobile device. In VR, user interaction technology is important, but various user interface methods is still lacking. Most of the interaction technologies are hand touch screen touch or motion recognition. We propose a new interface technology that can interact with VR contents in real time using user's mouth-wind method with acceleration sensor. The direction of the mouth-wind is determined using the angle and position between the user and the mobile device, and the control position is adjusted using the acceleration sensor of the mobile device. Noise included in the size of the mouth wind is refined using a simple average filter. In order to demonstrate the superiority of the proposed technology, we show the result of interacting with contents in game and simulation in real time by applying control position and mouth-wind external force to the game.