• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1307-1313
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• 2018

In recent years, there have been frequent occurrences of collapsing buildings and tilting accidents due to frequent earthquakes and aging of buildings. Various methods have been proposed to prevent disasters on these buildings. In this paper, we propose a system that provides an indication of anomalous phenomena such as collapse and tilting of buildings by real-time monitoring of IoT(Internet of Things) based architectural anomalies. The MEMS sensor is based on the inclinometer sensor and the accelerometer sensor, transmits the detected data to the server in real time, accumulates the data, and provides the service to cope when the set threshold value is different. It is possible to evacuate and repair the collapse and tilting of the building by warning the occurrence of the upper threshold event such as the collapse and tilting of the building.

• Journal of Navigation and Port Research
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• v.35 no.10
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• pp.785-791
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• 2011

This paper describes the evaluation and selection of MEMS(Micro-Elect Mechanical System) based inertial sensor to fit to implement the Inertial Measurement Unit(IMU) for a small-sized vessel at sea. At first, the error model and the noise model of the inertial sensors are defined with Euler's equations and then, the inertial sensor evaluation is carried out with Allan Variance techniques and Monte Carlo simulation. As evaluation results for the five sensors, ADIS16405, SAR10Z, SAR100Grade100, LIS344ALH and ADXL103, the combination of gyroscope and accelerometer of ADIS16405 is shown minimum error having around 160 m/s standard deviation of velocity error and around 35 km standard deviation of position error after 600 seconds. Thus, we select the ADIS16405 inertial sensor as a MEMS-based inertial sensor to implement IMU and, the error reducing method is also considered with the search for reference papers.

• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.54-64
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• 2013

In this study, we developed a falling recognition system to transmit SMS data through CDMA communication using a three axises acceleration sensor and a two axises gyro sensor. 5 healthy men were selected into a control group, and the fall recognition system using the three axises acceleration sensor and the two axises gyro sensor was devised to conduct an experiment. The system was attached to the upper of their sternum. According to the experiment protocol, the experiment was carried out 3 times repeatedly divided into 3 specific protocols: falling during gait, falling in stopped state, and falling in everyday life. Data obtained in the falling recognition system and LabVIEW 8.5 were used to decide if falling corresponds to that regulated in an analysis program applying an algorithm proposed in this study. In addition, results from falling recognition were transmitted to designated cellular phone in a SMS (Shot Message Service) form. These research results show that an erroneous detection rate of falling reached 19% in applying an acceleration signal only; 6% in applying an angular velocity; and 2% in applying a proposed algorithm. Such finding suggests that an erroneous detection rate of falling is improved when the proposed algorithm is applied incorporated with acceleration and angular velocity. In this study therefore, we proposed that a falling recognition system implemented in this study can make a contribution to the recognition of falling of the aged or the disabled.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.158-163
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• 2013

The fusion of the GPS (Global Positioning System) and DR (Dead Reckoning) is widely used for position and latitude estimation of vehicles such as a mobile robot, aerial vehicle and marine vehicle. Among the many types of aerial vehicles, grater focus is given on the quad-rotor and accuracy of the position information is becoming more important. In order to exactly estimate the position information, we propose the fusion method of GPS and Gyroscope sensor using the DEKF (Dual Extended Kalman Filter). The DEKF has an advantage of simultaneously estimating state value and a parameter of dynamical system. It can also be used even if state value is not available. In order to analyze the performance of DEKF, the computer simulation for estimating the position, the velocity and the angle in a circle trajectory of quad-rotor was done. As it can be seen from the simulation results using own proposed DEKF instead of EKF on own fusion method in the navigation of a quad-rotor gave better performance values.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.3
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• pp.141-150
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• 2015

In this study, a Global Navigation Satellite System (GNSS) / Inertial Navigation System (INS) / odometer / barometer integrated navigation system that uses a commercial navigation device including Micro Electro Mechanical Systems (MEMS) accelerometer and gyroscope in addition to GNSS, odometer information obtained from a vehicle, and a separate MEMS barometer sensor was implemented, and the performance was verified. In the case of GNSS and GNSS/INS integrated navigation system that are generally used in a navigation device, the performance would deteriorate in areas where GNSS signals are not available. Therefore, an integrated navigation system that calculates a better navigation solution in areas where GNSS signals are not available compared to general GNSS/INS by correcting the velocity error of GNSS/INS using an odometer and by correcting the cumulative altitude error of GNSS/INS using a barometer was suggested. To verify the performance of the navigation system, a commercial navigation device (Softman, Hyundai Mnsoft, http://www.hyundai-mnsoft.com) and a barometer sensor (ST Company) were installed at a vehicle, and an actual driving test was performed. To examine the performance of the algorithm, the navigation solutions of general GNSS/INS and the GNSS/INS/odometer/barometer integrated navigation system were compared in an area where GNSS signals are not available. As a result, a navigation solution that has a smaller position error than that of GNSS/INS could be obtained in the area where GNSS signals are not available.

• Advances in aircraft and spacecraft science
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• v.4 no.1
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• pp.53-64
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• 2017

Aerospace Launch Vehicles (ALV) are generally designed with high reliability to operate in complete security through fault avoidance practices. However, in spite of such precaution, fault occurring is inevitable. Hence, there is a requirement for on-board fault recovery without significant degradation in the ALV performance. The present study develops an advanced fault recovery strategy to improve the reliability of an Aerospace Launch Vehicle (ALV) navigation system. The proposed strategy contains fault detection features and can reconfigure the system against common faults in the ALV navigation system. For this purpose, fault recovery system is constructed to detect and reconfigure normal navigation faults based on the sliding mode observer (SMO) theory. In the face of pitch channel sensor failure, the original gyro faults are reconstructed using SMO theory and by correcting the faulty measurement, the pitch-rate gyroscope output is constructed to provide fault tolerant navigation solution. The novel aspect of the paper is employing SMO as an online tuning of analytical fault recovery solution against unforeseen variations due to its hardware/software property. In this regard, a nonlinear model of the ALV is simulated using specific navigation failures and the results verified the feasibility of the proposed system. Simulation results and sensitivity analysis show that the proposed techniques can produce more effective estimation results than those of the previous techniques, against sensor failures.

• KIISE Transactions on Computing Practices
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• v.23 no.3
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• pp.148-155
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• 2017

In this paper, we develop a new system to estimate the step count for a smartphone user. The system analyzes data obtained from the accelerometer, magnetic sensor, and gyroscope of an android smartphone to extract pattern information of human steps. We conduct an experiment and evaluation to confirm that the proposed system successfully estimates the number of steps with 96% accuracy when hand-held and 95.5% accuracy when in-pocket. In addition, we found that detection errors were caused by human motions such as touching the screen, shaking the device up and down, sitting up and sitting down, and waving the phone around.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.1048-1050
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• 2013

Mobile devices or smartphones are rapidly becoming the central computer and communication network device. Recently, smartphones are programmable and come with a growing set of cheap powerful embedded sensors, such as an accelerometer, digital compass, gyroscope, GPS, microphone, and camera. In this paper, we discuss the wireless gas sensing service architectural and develope the gas sensor monitoring services using smartphone and web server.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.430-433
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• 2018

This paper proposes the Kalman filter (KF) with optical flow method to estimate the position and the velocity of unmanned aerial vehicles (UAVs) in the absence of global positioning system (GPS). A downward-looking camera, a gyroscope and an ultrasonic sensor are fused to compensate the measurement from optical-flow method. To overcome the problem of dealing with noise in onboard sensors, the KF is incorporated to efficiently predict the velocity and estimate the position. Basic mechanisms of optical flow and the KF are introduced and experiments are conducted to show how the techniques involved improve the estimations.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.473-482
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• 2024

This study utilized virtual reality to construct a simulated public restroom environment to identify potential hazards. The objective was to discern actual risks in real-world public restrooms through this virtual setup. During the virtual restroom experience, data from the built-in 3-axis accelerometer and gyroscope sensors of testor's smart phones were collected. Analysis of this data helped in identifying spatio temporal factors impacting the users. The determination of these factors as risk elements was based on an evaluation algorithm grounded in data analysis.