• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1653-1659
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• 2022

Virtual reality content provides users with a high sense of immersion by using HMD devices. However, while wearing the HMD device, it is difficult to determine the user's location or distance from obstacles, resulting in injuries due to physical collisions. In this paper, we propose a reminder module to prevent accidents by notifying the risk of collision with obstacles while wearing the HMD device. The proposed module receives the user's state from the acceleration and gyro sensor and determines the motion that is likely to cause a collision. If there is an obstacle in the expected collision range, a buzzer sounds to the wearer. As a result of the experiment, the accuracy of obstacle detection in the state of wearing the HMD was 86.6% in the 1st stage and 83.3% in the 2nd stage, confirming the performance of the accident prevention reminder.

• Journal of Practical Engineering Education
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• v.16 no.4
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• pp.491-497
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• 2024

Over the past five years, the proportion of patients with arrhythmia heart disease among teenagers and those in their 20s has been increasing. Heart disease has consistently remained the second leading cause of death in Korea and as the number has increased, electrocardiogram testing for arrhythmia has become important. However, specialized electrocardiogram medical devices are economically burdensome and are difficult to store individually in hospitals due to their large size and difficulty in operation. Testing is conducted through visits. Therefore, it is essential to enable individuals to perform ECG self-examinations using an Arduino-based ECG sensor that is affordable and easy to use in daily life, so that arrhythmia can be identified through individual ECG measurement. In this study, data is measured using an electrocardiogram sensor (AD8232), and changes in bio signals are visually provided through real-time monitoring, allowing users to make intuitive decisions and at the same time understand test results. To safeguard sensitive personal information, we have developed a web service that provides individual heart disease and customized health guides that can protect personal information through web vulnerability security using session and user authentication and SSL.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.489-494
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• 2020

We propose to designs and to implements a robot analyzing the risk of occurrence of mental disorder of single-person households' workers through the facial expression-detecting system. Due to complex social factors, the number and proportion of single-person households continues to increase. In addition, contrast to the household of many family members, the prevalence of mental disorder among single-person household varies greatly. Since most patients with mental can not detect the disease on their own, counseling and treatment with doctors are often ignored. In this study, we design and implement a robot analyzing the risk of mental disorder of single-person households workers by constructing a system with Q.bo One, a social robot created by Thecorpora. Q.bo One is consisted of Arduino, ar raspberry pie, and other sensors designed to detect and respond to sensors in the direction users want to implement. Based on the DSM-5 provided by the American Psychiatric Association, the risk of mental disorder occurrence was specified based on mental disorder. Q.bo One analyzed the facial expressions of the subjects for a week or two to evaluate depressive disorder, anxiety disorder. If the mental disorder occurrence risk is high, Q.bo One is designd to inform the subject to counsel and have medical treatment with a specialist.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.537-542
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• 2022

There is a limit to the current indoor air quality (IAQ) monitoring method using fixed sensors and devices. A mobile robot for IAQ monitoring was developed by mounting IAQ monitoring sensors on a small multi-legged robot to minimize vibration and protect the sensors from vibration while robot moves. The developed mobile robot used a simple gait mechanism to enable the robot to move forward, backward, and turns only with the combination of forward and reverse rotation of the two DC motors. Due to the simple gait mechanism, not only IAQ data measurements but also gait motion control were processed using a single Arduino board. Because the mobile robot has small number of electronic components and low power consumption, a relatively low-capacity battery was mounted on the robot to reduce the weight of the battery. The weight of mobile robot is 1.4kg including links, various IAQ sensors, motors, and battery. The gait and turning speed of the mobile robot was measured at 3.75 cm/sec and 14.13 rad/sec. The maximum height where the robot leg could reach was 33 mm, but the mobile robot was able to overcome the bumps up to 24 mm.

• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.67-78
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• 2022

Interest in bio-signal monitoring of wearable devices is increasing significantly as the next generation needs to develop new devices to dominate the global market of the information and communication technology industry. Accordingly, this research developed a resistive textile strain sensor through a wetting process in a single-wall carbon nanotube dispersion solution using an E-Band with low hysteresis. To measure the resistance signal in the E-Band to which electrical conductivity is applied, a universal material tester, an Arduino, and LCR meters that are microcontroller units were used to measure the resistance change according to the tensile change. To effectively handle various noises generated due to the characteristics of the fabric textile strain sensor, the filter performance of the sensor was evaluated using the moving average filter, Savitsky-Golay filter, and intermediate filters of signal processing. As a result, the reliability of the filtering result of the moving average filter was at least 89.82% with a maximum of 97.87%, and moving average filtering was suitable as the noise filtering method of the textile strain sensor.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.301-307
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• 2023

Deep learning requires building a deep neural network, collecting a large amount of training data, and then training the built neural network for a long time. If training does not proceed properly or overfitting occurs, training will fail. When using deep learning tools that have been developed so far, it takes a lot of time to collect training data and learn. However, due to the rapid advent of the mobile environment and the increase in sensor data, the demand for real-time deep learning technology that can dramatically reduce the time required for neural network learning is rapidly increasing. In this study, a real-time deep learning system was implemented using an Arduino system equipped with a fine dust sensor. In the implemented system, fine dust data is measured every 30 seconds, and when up to 120 are accumulated, learning is performed using the previously accumulated data and the newly accumulated data as a dataset. The neural network for learning was composed of one input layer, one hidden layer, and one output. To evaluate the performance of the implemented system, learning time and root mean square error (RMSE) were measured. As a result of the experiment, the average learning error was 0.04053796, and the average learning time of one epoch was about 3,447 seconds.

• Journal of Bio-Environment Control
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• v.29 no.2
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• pp.141-152
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• 2020

The rapid on-site measurement of hydroponic nutrients allows for the more efficient use of crop fertilizers. This paper reports on the development of an embedded on-site system consisting of multiple ion-selective electrodes (ISEs) for the real-time measurement of the concentrations of macronutrients in hydroponic solutions. The system included a combination of PVC ISEs for the detection of NO₃, K, and Ca ions, a cobalt-electrode for the detection of H₂PO₄, a double-junction reference electrode, a solution container, and a sampling system consisting of pumps and valves. An Arduino Due board was used to collect data and to control the volume of the sample. Prior to the measurement of each sample, a two-point normalization method was employed to adjust the sensitivity followed by an offset to minimize potential drift that might occur during continuous measurement. The predictive capabilities of the NO₃ and K ISEs based on PVC membranes were satisfactory, producing results that were in close agreement with the results of standard analyzers (R² = 0.99). Though the Ca ISE fabricated with Ca ionophore II underestimated the Ca concentration by an average of 55%, the strong linear relationship (R² > 0.84) makes it possible for the embedded system to be used in hydroponic NO₃, K, and Ca sensing. The cobalt-rod-based phosphate electrodes exhibited a relatively high error of 24.7±9.26% in the phosphate concentration range of 45 to 155 mg/L compared to standard methods due to inconsistent signal readings between replicates, illustrating the need for further research on the signal conditioning of cobalt electrodes to improve their predictive ability in hydroponic P sensing.

• Journal of the Korean Society of Radiology
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• v.14 no.1
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• pp.15-22
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• 2020

PET(Positron Emission Tomography) devices are used as PET/CT or PET/MRI devices fused with the devices of CT or MRI for obtaining anatomical information. Therefore, the devices are constructed in circular ring-type structure whose length of gantry(the main part of filming) becomes wider and the interior depth becomes longer in comparison to other common medical equipments. scintillator, one of the components in PET devices, is inside the gantry, and as it is consisted of crystal which is sensitive to the change of temperature and humidity, large temperature change can cause the scintillator to be damaged. Though scintillator located inside the gantry maintains temperature and humidity with a thermo-hygrostat, changes in temperature and humidity are expected due to structural reasons. The output value was measured by dividing the inside of the gantry of the PET/CT device into six zones, each of which an Adafruit BME 280 temperature and humidity sensor was placed at. A thermo-hygrostat keeps the temperature and humidity constant in the PET/CT room. As the measured value of temperature and humidity of the sensor was obtained, the measured value of temperature and humidity appeared in the thermohygrostat was taken at the same time. Comparing the average measured values of temperature and humidity measured at each six zones with the average values of the thermo-hygrostat results in a difference of 2.71℃ in temperature and 21.5% in humidity. The measured temperature and humidity of PET Gantry is out of domestic quality control range. According to the results of the study, if there is continuous change in temperature and humidity in the future, the aging of the scintillator mounted in the PET Gantry is expected to be aging, so it is necessary to find a way to properly maintain the temperature and humidity inside the Gantry structure.