• ETRI Journal
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• v.35 no.2
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• pp.356-359
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• 2013

We present a method for tracking and interaction based on hybrid sensing for virtual environments. The proposed method is applied to motion tracking of whole areas, including the user's occlusion space, for a high-precision interaction. For real-time motion tracking surrounding a user, we estimate each joint position in the human body using a combination of a depth sensor and a wand-type physical user interface, which is necessary to convert gyroscope and acceleration values into positional data. Additionally, we construct virtual contents and evaluate the validity of results related to hybrid sensing-based whole-body tracking of human motion methods used to compensate for the occluded areas.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.4
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• pp.71-80
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• 2006

Strapdown Inertial navigation systems consist of an inertial sensor assembly(ISA), electronic modules to process sensor data, and a navigation computer to calculate attitude, velocity and position. In the ISA, most gryoscopes such as RLGs and FOGs, have digital output, but typical accelerometers use current as an analog output. For a high precision inertial navigation system, sufficient stability and resolution of the accelerometer board converting the analog accelerometer output into digital data needs to be guaranteed. To achieve this precision, the asymmetric error and A/D reset scale error of the accelerometer board must be properly compensated. If the relation between the acceleration error and the errors of boards are exactly known, the compensation and estimation techniques for the errors may be well developed. However, the A/D Reset scale error consists of a pulse-train type term with a period inversely proportional to an input acceleration additional to a proportional term, which makes it difficult to estimate. In this paper, the effects on the acceleration output for auto-pilot situations and the effects of A/D reset scale errors during horizontal alignment are qualitatively analyzed. The result can be applied to the development of the real-time compensation technique for A/D reset scale error and the derivation of the design parameters for accelerometer board.

• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.11-18
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• 2010

In this paper, it introduced the device that was fabricated for monitoring sleeping positions of infants with 3-axis accelerometer. Sleep monitoring studies has been usually conducted two ways. To monitor sleeping posture by installing a camera and then recording of sleep in the sleeping room continuously is the first one. The other one is monitoring pressure sensor's results data for sleeping. Those two ways' benefits are that are able to get relatively accurate sleeping posture data but, there are many disadvantages like constraints of spaces and places, the installation of sensors or cameras, and high cost. In addition, it has a lot of problems that difficult to solve. For babies, it's not easy to apply, as well as uncomfortable. The proposed method uses a 3-axis accelerometer's X axis, Y axis, Z axis position output values in order to recognize the bad ground sleeping position that use of the buzzer alarm. This method uses a 3-axis acceleration sensor to measure the data and transmit sleeping posture using Bluetooth wireless in real time monitoring. The data is helpful for prevention safety hazard such as choked themselves when they slept back side on.

• Science of Emotion and Sensibility
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• v.20 no.3
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• pp.141-150
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• 2017

The purpose of this study was to analyze the effect of the shape and attached position of E-textile-based stretchable sensors on motion-sensing performance and to investigate the requirements for the optimal structure of clothes for sensing limb motions. An experimental garment was prepared with different sensor shapes, and attachment positions. A child subject, wearing the experimental garment, performed arm and leg bending and extension motions at $60^{\circ}$, $90^{\circ}$ and $120^{\circ}$ motion angles, at a rate of 60 deg/sec. The changes in voltage triggered by the stretching and contracting of the fabric-sensor were measured, and an acceleration sensor was utilized to verify that the experimental motions were correctly performed. Dummy arms and legs of a child were manufactured to perform an identical test, in order to compare the dummy results with the actual human body experiment results. The analysis showed that the reproducibility and reliability of the rectangular sensor, showing uniform and stable were higher than those of the boat-shaped sensor, in both the dummy and the human body experiments. The attachment position of the sensor was more reproducible and reliable when placed on 4 cm below the elbow and knee joints in the dummy test, when placed in the joints of the elbow and knee, in children experiment. The appropriate shapes and attached positions of the sensor for sensing the motions were analyzed, and the results proved that motion-sensing of the human body is possible by utilizing flexible fabric-sensors integrated into clothes.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.7-13
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• 2021

This paper presents an vulnerable road user (VRU) classification and tracking algorithm using vision and LiDAR sensor fusion method for urban autonomous driving. The classification and tracking for vulnerable road users such as pedestrian, bicycle, and motorcycle are essential for autonomous driving in complex urban environments. In this paper, a real-time object image detection algorithm called Yolo and object tracking algorithm from LiDAR point cloud are fused in the high level. The proposed algorithm consists of four parts. First, the object bounding boxes on the pixel coordinate, which is obtained from YOLO, are transformed into the local coordinate of subject vehicle using the homography matrix. Second, a LiDAR point cloud is clustered based on Euclidean distance and the clusters are associated using GNN. In addition, the states of clusters including position, heading angle, velocity and acceleration information are estimated using geometric model free approach (GMFA) in real-time. Finally, the each LiDAR track is matched with a vision track using angle information of transformed vision track and assigned a classification id. The proposed fusion algorithm is evaluated via real vehicle test in the urban environment.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.282-292
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• 2020

In order to minimize casualties from marine vessel accidents that occur frequently at home and abroad, it is important to ensure the safety of the passengers aboard the vessel in the event of an accident. There is an EPIRB system as a system for disaster preparedness in the marine situation currently on the market, but there is a problem that the price is very expensive. In order to overcome the cost problem, which is a disadvantage of previous system, LoRaWAN-based communication is used. LoRaWAN communication-based vessel positioning and risk detection system based on LoRaWAN communication transmits measurement data of each module using two Beacon and GPS modules to stably perform position measurement for both indoor and outdoor situations. The rider danger situation detection system can detect the safety status of the rider using the 3-axis acceleration sensor, collect data from the rider positioning system and the rider safety status detection system, and send to server using LoRa communication. When conducting communication experiments in the long-distance maritime situation and actual communication experiments using the implemented system, it was found that the two experiments showed over 90% communication success rate on average.

• Smart Structures and Systems
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• v.16 no.2
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• pp.295-328
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• 2015

In recent years the monitoring of structural behavior through acquisition of vibrational data has become common practice. In addition, recent advances in sensor development have made the collection of diverse dynamic information feasible. Other than the commonly collected acceleration information, Global Position System (GPS) receivers and non-contact, optical techniques have also allowed for the synchronous collection of highly accurate displacement data. The fusion of this heterogeneous information is crucial for the successful monitoring and control of structural systems especially when aiming at real-time estimation. This task is not a straightforward one as measurements are inevitably corrupted with some percentage of noise, often leading to imprecise estimation. Quite commonly, the presence of noise in acceleration signals results in drifting estimates of displacement states, as a result of numerical integration. In this study, a new approach based on a time domain identification method, namely the Unscented Kalman Filter (UKF), is proposed for correcting the "drift effect" in displacement or rotation estimates in an online manner, i.e., on the fly as data is attained. The method relies on the introduction of artificial white noise (WN) observations into the filter equations, which is shown to achieve an online correction of the drift issue, thus yielding highly accurate motion data. The proposed approach is demonstrated for two cases; firstly, the illustrative example of a single degree of freedom linear oscillator is examined, where availability of acceleration measurements is exclusively assumed. Secondly, a field inspired implementation is presented for the torsional identification of a tall tower structure, where acceleration measurements are obtained at a high sampling rate and non-collocated GPS displacement measurements are assumed available at a lower sampling rate. A multi-rate Kalman Filter is incorporated into the analysis in order to successfully fuse data sampled at different rates.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2586-2592
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• 2014

Lost fishing gears become a major cause of marine pollution, and many policy and technical efforts have been conducted for that. For efficient retrieving lost fishing gears in underwater, It is important to know the current position. Using GPS in the sub-sea environment is impossible and localization requires the use of special systems, and mobility due to water currents for underwater localization also has to be considered. In this paper, described with respect to the system for a self-generated location informations without using an external signal, such as a GPS and Sonar and storing them. Using the characteristics of the geomagnetic and INS principle, proposed informations and a way for estimating self position during movement. Embedded based system suggested and implemented in this study is tested for validating it's functionality.

• Advances in Automotive Engineering
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• v.1 no.1
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• pp.61-77
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• 2018

In this study, the effects of sitting position of the driver on the whiplash neck injury have been analyzed experimentally by using hybrid III series 50 percentile male crash test dummy. A testing platform consisting of vehicle ground, driver foot rest, driver seat and a 3-point seatbelt has been prepared. This testing platform and the instrumented crash test dummy are prepared for tests according to the Euro NCAP whiplash testing protocol. The prepared test set-up has been exposed to 3 different acceleration-time loading curves defined in the Euro NCAP whiplash testing protocol by performing sled tests. 9 different sled tests have been performed with the combinations of 3 different seating positions of the crash test dummy and 3 different acceleration-time loading curves. The sensor data obtained from the crash test dummy and high-speed videos taken are analyzed according to the injury assessments criteria defined in the Euro NCAP whiplash testing protocol and the criticality of the whiplash injury is defined. It is seen that the backset distance of the driver head with the headrest and the height difference of the top of the head of the driver with the headrest have a great importance on whiplash injuries.

• Journal of Advanced Navigation Technology
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• v.19 no.1
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• pp.74-79
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• 2015

In this paper, in order to improve the error is utilized to location tracking the smart sensor detects a walking information user, RSSI is to provide an indoor position tracking system that is capable of correcting an error in terms weak. The acceleration sensor is able to detect the activity in the user walking and detects the number of step and the moving distance using the same. The Direction sensor is utilized as a digital compass, to detect the moving direction of the user. As a result of detecting the walking information using the sensor, it can be showed that this proposed indoor positioning system has a high degree of accuracy for the number of steps and the movement direction. Therefore, this paper shows that the proposed technique can correct the error of the location information to be problem in the conventional indoor location system which uses the only Wi-Fi APs by estimating the user's movement direction and distance using the sensors in smartphone without an additional equipment and cost.