• Journal of the Semiconductor & Display Technology
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• v.9 no.2
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• pp.41-47
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• 2010

In this paper we suggest an improvement upon the previous method of estimating a body's attitude. This paper presents a method that overcomes the shortcomings of previous studies. Applying the method of separating the acceleration of gravity component from the accelerometer's output improves the performance of the attitude estimation and extends the scope. In order to apply the method of the attitude estimation in an actively moving body, a new acceleration value containing the acceleration of gravity is calculated. This paper also proposes the method which minimizes the estimation error in estimating the moving body's attitude which is changing rapidly. Finally, this paper suggests a method that detects the gyroscope's drift and compensates for this drift using accelerometer. Applying the method improves the performance of the attitude estimation.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.159-172
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• 2024

The number of healthcare products available for pets has increased in recent times, which has prompted active research into wearable devices for pets. However, the data collected through such devices are limited by outliers and missing values owing to the anomalous and irregular characteristics of pets. Hence, we propose pet behavior recognition based on a hybrid one-dimensional convolutional neural network (CNN) and long short- term memory (LSTM) model using pet wearable devices. An Arduino-based pet wearable device was first fabricated to collect data for behavior recognition, where gyroscope and accelerometer values were collected using the device. Then, data augmentation was performed after replacing any missing values and outliers via preprocessing. At this time, the behaviors were classified into five types. To prevent bias from specific actions in the data augmentation, the number of datasets was compared and balanced, and CNN-LSTM-based deep learning was performed. The five subdivided behaviors and overall performance were then evaluated, and the overall accuracy of behavior recognition was found to be about 88.76%.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.459-466
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• 2000

In this paper, we propose an attitude controller for an unstructured object using CMG(Control Moment of Gyro) subsystem, which has a stabilizer function. The CMG subsystem consists of one motor for spinning the wheel and the other motor for turning the outer gimbal. While the wheel of CMG subsystem is spinning at high speed, applying force to the spin axis of the wheel leads the torque about the vertical axis. We utilize the torque to control the attitude of object in this study. For the stabilizer function, in additiion, holding the load at the current position, the power applied to the gimbal motor of CMG will be cut, which result in the braking force to stop the load by gyro effect. However, due to the gear reduction connected to outer gimbal, slow load motion cannot generate the braking force. Thus, in this study, we are willing to make a holding force by applying control power to the gimbal motor from the signal of piezoelectric gyroscopic sensor that detected the angular velocity of the load. These two features are demonstrated in experiment, carrying a beam with crane. As a result, load was started to rotate by controlling gimbal positiion and was stopped by turning off the gimbal power. Moreover, slow movement of the load was also rejected by additional control with gyroscopic sensor.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.1-9
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• 2018

A keyboard system for hands-free virtual reality head mounted display using electrooculogram (EOG) signal which occurs during the eye-blinking is proposed. This system consists of display device, gyroscope sensor, gravity sensor and electro-encephalogram (EEG) sensor, and it is implemented with Unity3D engine for system control and graphic processing. If the input language of proposed keyboard system is Korean, i.e. Hangul, the Chonjiin keyboard method is utilized; but for the English spelling, numbers or special characters, $3{\times}4$ keyboard method is used in order to solve the spatial problem. By the implemented method, it can be verified that the user can handle the keyboard input of virtual reality head mounted display with only neck movement and EOG, instead of using hands.

• Journal of Ocean Engineering and Technology
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• v.31 no.2
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• pp.164-169
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• 2017

Studies were performed on an ARS using SDINS's RLG and the geomatic sensor. To develop the ARS, experiments were performed to determine the characteristics of the RLG and geomatic sensor. Based on the results, to reduce the angular position errors of the RLG, which accumulate from the angular velocity data, an algorithm was studied that uses the Extended Kalman filter (EKF) to compensate the RLG data and geomatic sensor data. To verify the performance of the developed algorithm for reducing the cumulative angular errors, experiments that included the developed EKF were performed. Through these, it was shown that a drastic reduction in the angular errors of the RLG were achieved.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.47-54
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• 2022

In this paper, MEMS embedded system design implemented the sensor events via analyzing the characteristics that dynamically happened to an abnormal status in power IoT environments in order to guarantee a maintainable operation. We used three kinds of tools in this paper, at first Bluetooth Low Energy (BLE) technology which is a suitable protocol that provides a low data rate, low power consumption, and low-cost sensor applications. Secondly LSM6DSOX, a system-in-module containing a 3-axis digital accelerometer and gyroscope with low-power features for optimal motion. Thirdly BM1422AGMV Digital Magnetometer IC, a 3-axis magnetic sensor with an I2C interface and a magnetic measurable range of ±120 uT, which incorporates magneto-impedance elements to detect the magnetic field when the current flowed in the power devices. The proposed MEMS system was developed based on an nRF5340 System on Chip (SoC), previously compared to the standalone embedded system without bluetooth technology via mobile App. And also, MEMS embedded system with BLE 5.0 technology broadcasted the MEMS system status to Android mobile server. The experiment results enhanced the performance of MEMS system design by combination of sensors, BLE technology and mobile application.

• Advances in nano research
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• v.15 no.2
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• pp.155-163
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• 2023

Exercise is beneficial to the body in some ways. It is vital for people who have heart problems to perform exercise according to their condition. This paper describes how an Android platform can provide early warnings of fatigue during wushu exercise using Photoplethysmography (PPG) signals. Using the data from a micro-electro-mechanical system (MEMS) gyroscope to detect heart rate, this study contributes an algorithm to determine a user's fatigue during wushu exercise. It sends vibration messages to the user's smartphone device when the heart rate exceeds the limit or is too fast during exercise. The heart rate monitoring system in the app records heart rate data in real-time while exercising. A simple pulse sensor and Android app can be used to monitor heart rate. This plug-in sensor measures heart rate based on photoplethysmography (PPG) signals during exercise. Pulse sensors can be easily inserted into the fingertip of the user. An embedded microcontroller detects the heart rate by connecting a pulse sensor transmitted via Bluetooth to the smartphone. In order to measure the impact of physical activity on heart rate, Wushu System tests are conducted using various factors, such as age, exercise speed, and duration. During testing, the Android app was found to detect heart rate with an accuracy of 95.3% and to warn the user when their heart rate rises to an abnormal level.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.567-568
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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 algorithm 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 multi-advanced 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 event such as the collapse and tilting of the building.

• Journal of Advanced Navigation Technology
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• v.21 no.1
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• pp.126-131
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• 2017

This paper designs a smart safety measurement system with Bluetooth beacon sensor nodes that can provide risk detection and evacuation/countermeasure services. The Bluetooth beacon sensor nodes is easily able to be attached to old building wall or construction or civil structure with potential danger. The proposed smart safety measurement system transmits various sensor data such as acceleration, gyroscope, geomagnetic, pressure, altitude, temperature, humidity at the spot where Bluetooth beacon sensor nodes are installed, and we can use them for risk perception, prediction, and warning services. To verify the effectiveness of the proposed system, we performed filed tests which showed that measured displacement values of precast retaining walls were within the permitted displacement value of 38.5 mm.

• 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.