• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.83-90
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• 2018

In this paper, we propose an algorithm for analyzing personal health log information in android environment, providing personal health log information in android environment, providing personalized exercise information and monitoring the condition of pedestrians. Personal health log data collection is performed based on raw data of user using MPU6050 sensor based on Arduino. Noise was removed and age threshold was applied to distinguish movement information. In addition, to protect personal information, safety is enhanced by providing anti-compilation prevention and encryption/decryption of APK file, and the result of movement information collection is measured according to sensor location. Experimental results showed that the MPU6050 sensor mounted one the ankle wsa measured 98.97% more accurately then the wrist. In addition, the loading time of SEED 128 bit encryption based DEX file has the average time of 0.55ms, minimizing the overhead.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.139-148
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• 2020

Walking is one of the most natural and repetitive actions we do in our daily lives. However, many modern people have problems with shoulders, back and spine due to incorrect walking habits. Therefore, it is becoming important to diagnose and correct wrong walking habits, for example, in-toeing, out-toeing, etc. early, which can be a precursor to various diseases. In this study, we developed the system to diagnose and prevent incorrect gait by grasping and analyzing the angle and muscle activity of the foot according to the typical wrong gait type through MPU 6050 acceleration sensor and the surface EMG sensor. Through a smartphone, numerical and visualization screens based on walking can be used to represent the angle of the feet, real-time EMG values, and even the number of steps. The correction effect was enhanced by improving the cognitive ability through a system that allows individuals to easily diagnose gait through smart devices and improve them according to their own problems.

• Journal of Platform Technology
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• v.6 no.2
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• pp.3-9
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• 2018

Recently VR environment is used in many areas including mobile learning, smart factory. However HMD(head-mounted display) is required to a dedicated and expensive system with high-end specification. When designing a VR system, it is needed to handle performance, mobility and usability. Many VR applications need to handle diverse sensors and user inputs continuously in a streaming manner. In this paper we design a VR mobile platform and implement a low-cost mobile VR HMD running on the platform. The VR HMD supports 3D contents delivery in a mobile manner. It is used to detect the motion detection based on angle value of a VR player from accelerator and gyro sensor. The MPU-6050, 6-axis sensor, is used to get a sensory value and the sensory value is taken as an input to a VR rendering server on a Unity game engine that is generated 3D images.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.283-288
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• 2024

In this paper, a novel mechanism for overcoming obstacles is studied by designing an All-Directional RC car for obstacle traversal and creating test courses with various obstacles. We propose an algorithm for controlling the RDS3115 servo motor and utilize a gyro sensor to detect the incline of various obstacle terrains, adjusting the servo motor's angle to enable the RC car to navigate the terrain. Through terrain experiments in the test course, we determined the most suitable RC car turning angles for traversing all obstacle terrains created in the experimental terrain.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.2
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• pp.31-37
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• 2016

Falling situations are extremely critical events for the elderly person who requires timely and adequate emergency service. For the case of emergency, the information of falling and its direction can be used as an important information for the first aid treatment of the injured person. In this paper, a falling detection system which can pinpoint the falling event with the falling direction is implemented. In order to detect the fall situation, a single gyroscope (MPU-6050) is used in the developed system. The fall detection algorithm that can classify 8 different fall directions such as front, back, left, right and in between falls is proposed. The direction of the fall is decided by examining the acceleration values of X and Y directions of the sensor. It is shown that the proposed algorithm successfully detects the falling event and the falling direction with probability of 97% for a selected value of acceleration threshold.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.4
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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 Internet of Things and Convergence
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• v.10 no.4
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• pp.27-33
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• 2024

As of 2023, the number of accident victims in the domestic construction industry is 26,829, ranking second only to other businesses (service industries). The accident types of casualties in all industries were falls (29,229 people), followed by falls (14,357 people). Based on the above data, this study attaches sensors to hard hats and insoles to predict fall accidents that frequently occur at construction sites, and proposes smart safety equipment that applies a random forest algorithm based on the data collected through this. The random forest model can determine fall accidents in real time with high accuracy by generating multiple decision trees and combining the predictions of each tree. This model classifies whether a worker has had a fall accident and the type of behavior through data collected from the MPU-6050 sensor attached to the hard hat. Fall accidents that are primarily determined from hard hats are secondarily predicted through sensors attached to the insole, thereby increasing prediction accuracy. It is expected that this will enable rapid response in the event of an accident, thereby reducing worker deaths and accidents.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.4
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• pp.591-598
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• 2017

The changes of technology and the size of markets for unmaned aerial vehicle are getting bigger presently. Damage happens because of user's poor operation since accesses to the drones are easy. To minimize the damage, drone's stabilized flight skills are required, and controlling the motor to balanced speed is also needed. Thus, the essay shows that we use Arduino as a main control device for controlling a drone, and used acceleration sensor and gyro sensor for the drone stabilization. Also, we made it able to hover at a certain height by using a sonar sensor. We also controlled a drone by using an Android application, and made the drone hover stably at 0~2 meters.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.666-671
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• 2019

The flight controller(FC) used in small-sized drone was developed as simple structure does not perform complex operations because it uses different MCU with large-sized drone. Also, the balance control of small-sized drone should be simpler than Kalman filter using complex filter and the method using Complementary filter has relatively more operations. So, the method to realize the balance control on small-sized drone effectively using two-track control operating as proper method for above is suggested in this research. This method is a system maintaining effective balance with simple structure and less operations by operating adaptively for the unbalance of the drone with the acceleration sensor with the advantage which performing accurate correction by data processing for long term change and gyroscope sensor maintaining the balance of the drone by data processing for short term change. It is confirmed that stable operation was performed mostly based on the test result for repeatable test more than 100 times using two-track control and it maintained normal state operation more than 98% excluding the difficulty of maintaining normal operation when meets sudden and rapid wind yet.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.77-83
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• 2019

Major causes of industrial accidents include falls and gas leak. The existing safety helmet and smart device combination products are focused on convenience, so the functions to prevent such accidents are insufficient. We developed a smart helmet focusing on fall accident detection and gas leak detection. We also developed management system to manage workers efficiently. Its core function is to detect dangerous conditions of employees, to communicate with managers and to confirm the situations of workers. The effectiveness of the combustible gas measurement capability was verified through experiments. However, since a significant amount of power consumption is founded due to continuous operation of the board and the sensor, countermeasures such as replacing with a large capacity battery are required.