• Journal of Information Technology Applications and Management
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• v.28 no.3
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• pp.59-75
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• 2021

This study aims to establish a foundation for autonomous driving on campus and communication of abundant university information in the HCI environment in a VR environment where college freshmen can freely travel around campus facilities. The purpose of this study is to develop a three-dimensional VR-style campus tour system to establish a media environment to provide abundant university information guidance services to freshmen in non-face-to-face situations. This study designed a three-dimensional virtual reality campus tour system to solve the problem of discontinuity in which VR360 filming space does not lead to space like reality, and to solve many problems of expertise in VR technology by constructing an integrated production environment of tour system. We aim to solve the problem of inefficiency, which requires a large amount of momentum in virtual space, by constructing a GUI that utilizes the motion of the field of view focus. The campus environment was designed as a three-dimensional virtual reality using a three-dimensional graphic design. In non-face-to-face situations, college freshmen freely transformed the HMD VR device, smartphone, FPS operation mode of the gyroscope sensor. The design elements of the three-dimensional virtual reality campus tour system were classified as ①Visualization of factual experiences, ②Continuity of space movement, ③Operation, automatic operation mode, ④Natural landscape animation, ⑤Animation according to wind direction, ⑥Actual space movement mode, ⑦Informatization of spatial understanding, ⑧GUI by experience environment, ⑨Text GUI by building, ⑩VR360, 3D360 Studio Environment, ⑪Three-dimensional virtual space coupling block module, ⑫3D360-3D Virtual Space Transmedia Zone, ⑬Transformable GUI(VR Device Dual Viewer-Gyro Sensor Full Viewer-FPS Operation Viewer) and an integrated production environment was established with each element. It is launched online (http://vautu.com/u1) by constructing a GUI for free driving mode and college information screens to adapt to college life for freshmen, and designing an environment that can be used simultaneously by current media such as PCs, Android, and iPads. Therefore, it conducted user research, held a development presentation, a forum on excellence in university innovation support projects, and applied it as a system on the website of a particular university. College freshmen will be able to experience university information directly from the web and app to the virtual reality campus environment.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.171-180
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• 2023

The three major sleep disorders in Korea are snoring, sleep apnea, and insomnia. Lack of sleep is the root of all diseases. Some of the most serious potential problems associated with sleep deprivation are cardiovascular problems, cognitive impairment, obesity, diabetes, colitis, prostate cancer, etc. To solve these problems, the Korean government provided low-cost national health insurance benefits for polysomnography tests in July 2018. However, insomnia patients still have problems getting treated in terms of time, space, and economic perspectives. Therefore, it would be better for insomnia patients to be allowed to test at home. The measuring device can measure six biosignals (eye movement, tossing and turning, body temperature, oxygen saturation, heart rate, and audio). A gyroscope sensor (MPU9250, InvenSense, USA) was used for eye movement, tossing, and turning. The input range of the sensor was in 258°/sec to 460°/sec, and the data range was in the input range. Body temperature, oxygen saturation range, and heart rate were measured by a sensor (MAX30102, Analog Devices, USA). The body temperature was measured in 30 ℃ to 45 ℃, and the oxygen saturation range was 0% for the unused state and 20 % to 90 % for the used state. The heart rate measurement range was in 40 bpm to 180 bpm. The measurement of audio signal was performed by an audio sensor (AMM2742-T-R, PUIaudio, USA). The was -42 dB ±1 dB frequency range was 20 Hz to 20 kHz. The measured data was successfully received in wireless network conditions. The system configuration was consisted of a PC and a mobile app for bio-signal measurement and data collection. The measured data was collected by mobile phones and desktops. The data collected can be used as preliminary data to determine the stage of sleep and perform the screening function for sleep induction and sleep disturbances. In the future, this convenient sleep measurement device could be beneficial for treating insomnia.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.167-176
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• 2022

We designed a borehole deviation survey tool applicable for steel-cased holes, K-DEV, and developed a prototype for a depth of 500 m aiming to development of own equipment required to secure deep subsurface characterization technologies. K-DEV is equipped with sensors that provide digital output with verified high performance; moreover, it is also compatible with logging winch systems used in Korea. The K-DEV prototype has a nonmagnetic stainless steel housing with an outer diameter of 48.3 mm, which has been tested in the laboratory for water resistance up to 20 MPa and for durability by running into a 1-km deep borehole. We confirmed the operational stability and data repeatability of the prototype by constantly logging up and down to the depth of 600 m. A high-precision micro-electro-mechanical system (MEMS) gyroscope was used for the K-DEV prototype as the gyro sensor, which is crucial for azimuth determination in cased holes. Additionally, we devised an accurate trajectory survey algorithm by employing Unscented Kalman filtering and data fusion for optimization. The borehole test with K-DEV and a commercial logging tool produced sufficiently similar results. Furthermore, the issue of error accumulation due to drift over time of the MEMS gyro was successfully overcome by compensating with stationary measurements for the same attitude at the wellhead before and after logging, as demonstrated by the nearly identical result to the open hole. We believe that the methodology of K-DEV development and operational stability, as well as the data reliability of the prototype, were confirmed through these test applications.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.2
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• pp.60-67
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• 2015

The finite element (FE) model updating is a commonly used approach in civil engineering, enabling damage detection, design verification, and load capacity identification. In the FE model updating, acceleration responses are generally employed to determine modal properties of a structure, which are subsequently used to update the initial FE model. While the acceleration-based model updating has been successful in finding better approximations of the physical systems including material and sectional properties, the boundary conditions have been considered yet to be difficult to accurately estimate as the acceleration responses only correspond to translational degree-of-freedoms (DOF). Recent advancement in the sensor technology has enabled low-cost, high-precision gyroscopes that can be adopted in the FE model updating to provide angular information of a structure. This study proposes a FE model updating strategy based on data fusion of acceleration and angular velocity. The usage of both acceleration and angular velocity gives richer information than the sole use of acceleration, allowing the enhanced performance particularly in determining the boundary conditions. A numerical simulation on a simply supported beam is presented to demonstrate the proposed FE model updating approach.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.215-226
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• 2015

Normally, aero photography using UAV uses about 430 MHz bandwidth radio frequency (RF) modem and navigates and remotely controls through the connection between UAV and ground control system. When using the exhausting method, it has communication range of 1-2 km with frequent cross line and since wireless communication sends information using radio wave as a carrier, it has 10 mW of signal strength limitation which gave restraints on life my distance communication. The purpose of research is to use communication technologies such as long-term evolution (LTE) of smart camera, Bluetooth, Wi-Fi and other communication modules and cameras that can transfer data to design and develop automatic shooting system that acquires images to UAV at the necessary locations. We conclude that the android based UAV filming and communication module system can not only film images with just one smart camera but also connects UAV system and ground control system together and also able to obtain real-time 3D location information and 3D position information using UAV system, GPS, a gyroscope, an accelerometer, and magnetic measuring sensor which will allow us to use real-time position of the UAV and correction work through aerial triangulation.

• Spatial Information Research
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• v.19 no.5
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• pp.87-96
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• 2011

Recently mobile users can access to internet using smart phone at any place and any time, through which they can search and share information. In addition, as the sensors with high-tech functions become cheaper and miniaturized along with the development of MEMS (micro-electo mechanical systems) technology, the extent to utilize smart phone is increasing. Smart phone is equipped with various sensors such as high-resolution camera, GPS, gyroscope and magnetic sensor, which is an appropriate system configuration for remote monitoring research using camera. The remote monitoring system requires camera for video and internet network to send video, for which it has a limitation that it is influenced by the monitoring location. This study is aimed to design and develop the monitoring app. which can be remotely monitored using smart phone technology. The developed monitoring app was designed to take images of ROI (region of interest) within the specified time and to automatically send the images to the server. The developed app. is also possible to be remotely controlled by SMS (short message service). The monitoring proposed in this study can take high-resolution images using CMOS built in the smart phone and send the images and information to the server automatically at any place and any time using 3G and Wi-Fi networks.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.04a
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• pp.842-848
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• 2013

Developments of Solid-State Gyroscopy during last decades are impressive and were based on thin-walled shell resonators like HRG or CRG made from fused quartz or leuko-sapphire. However, a number of design choices for inertial-grade gyroscopes, which can be used for high-g applications and for mass- or middle-scale production, is still very limited. So, considerations of fundamental physical effects in solids that can be used for development of a miniature, completely solid-state, and lower-cost sensor look urgent. There is a variety of different types of bulk acoustic (elastic) waves (BAW) in anisotropic solids. Shear waves with different variants of their polarization have to be studied especially carefully, because shear sounds in glasses and crystals are sensitive to a turn of the solid as a whole, and, so, they can be used for development of gyroscopic sensors. For an isotropic medium (for a glass or a fine polycrystalline body), classic Lame's theorem (so-called, a general solution of Elasticity Theory or Green-Lame's representation) has been modified for enough general case: an elastic medium rotated about an arbitrary set of axes. Travelling, standing, and mixed shear waves propagating in an infinite isotopic medium (or between a pair of parallel reflecting surfaces) have been considered too. An analogy with classic Foucault's pendulum has been underlined for the effect of a turn of a polarizational plane (i.e., an integration effect for an input angular rate) due to a medium's turn about the axis of the wave propagation. These cases demonstrate a whole-angle regime of gyroscopic operation. Single-crystals are anisotropic media, and, therefore, to reflect influence of the crystal's rotation, classic Christoffel-Green's tensors have been modified. Cases of acoustic axes corresponding to equal velocities for a pair of the pure-transverse (shear) waves have of an evident applied interest. For such a special direction in a crystal, different polarizations of waves are possible, and the gyroscopic effect of "polarizational precession" can be observed like for a glass. Naturally, formation of a wave pattern in a massive elastic body is much more complex due to reflections from its boundaries. Some of these complexities can be eliminated. However, a non-homogeneity has a fundamental nature for any amorphous medium due to its thermodynamically-unstable micro-structure, having fluctuations of the rapidly-frozen liquid. For single-crystalline structures, blockness (walls of dislocations) plays a similar role. Physical nature and kinematic particularities of several typical "drifts" in polarizational BAW gyros (P-BAW) have been considered briefly too. They include irregular precessions ("polarizational beats") due to: non-homogeneity of mass density and elastic moduli, dissymmetry of intrinsic losses, and an angular mismatch between propagation and acoustic axes.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.2
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• pp.161-168
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• 2015

In this paper, we present an inertial sensor-based gait distance measurement system using accelerometer, gyroscope, and magnetometer. To minimize offset and gain error of inertial sensors, we performed the calibration using the self-made calibration jig with 9 degrees of freedom. For measuring accurate gait distance, we used gradient descent algorithm to remove gravity error and used analysis of gait pattern to remove drift error. Finally, we measured a gait distance by double-integration of the error-removed acceleration data. To evaluate the performance of our system, we walked 10m in a straight line indoors to observe the improvement of removing error which compared un-calibrated to calibrated data. Also, the gait distance measured by the system was compared to the measurement of the Vicon motion capture system. The evaluation resulted in the improvement of $31.4{\pm}14.38%$(mean${\pm}$S.D.), $78.64{\pm}10.84%$ and $69.71{\pm}26.25%$ for x, y and z axis, respectively when walked in a straight line, and a root mean square error of 0.10m, 0.16m, and 0.12m for x, y and z axis, respectively when compared to the Vicon motion capture system.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.68-77
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• 2021

In this paper, a GPS/MEMS IMU integrated navigation receiver module capable of operating in a high dynamic environment is designed and fabricated, and the results is confirmed. The designed module is composed of RF receiver unit, inertial measurement unit, signal processing unit, correlator, and navigation S/W. The RF receiver performs the functions of low noise amplification, frequency conversion, filtering, and automatic gain control. The inertial measurement unit collects measurement data from a MEMS class IMU applied with a 3-axis gyroscope, accelerometer, and geomagnetic sensor. In addition, it provides an interface to transmit to the navigation S/W. The signal processing unit and the correlator is implemented with FPGA logic to perform filtering and corrrelation value calculation. Navigation S/W is implemented using the internal CPU of the FPGA. The size of the manufactured module is 95.0×85.0×.12.5mm, the weight is 110g, and the navigation accuracy performance within the specification is confirmed in an environment of 1200m/s and acceleration of 10g.