• Title/Summary/Keyword: 센싱 웨어

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Wearable Sensing Device Design for Biological Monitoring (생체정보 모니터링을 위한 웨어러블 센싱 디바이스 디자인)

  • Lee, Jee Hyun;Lee, Eun Ji;Kim, Ji Eun;Kim, Yoolee;Cho, Sinwon
    • Journal of the Korean Society of Costume
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    • v.65 no.1
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    • pp.118-135
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    • 2015
  • In recent years, smart clothing had been developed in order to better detect and monitor physical movement of the patient, so that such activities such as location identification and biometric recognition could be done. However, most of the sensing devices of smart clothing were limited to smart sensing sports clothing and the designs did not consider the physical characteristics and the behavior of the wearer. Therefore, this study aimed to create an open protection system by developing a wearable sensing device for health monitoring and location information. For this purpose, this study developed eleven types of wearable sensing design that could be commercially sold and worn by people who needed their biological information to be constantly monitored. The study conducted four tests in order to develop three types of sensing devices for various sensing wears. The purpose of this study was to expand the user rang of smart sensing wears, and provide a foundation for the development of distinctive wearable sensing devices reflecting the user. Furthermore, contribute to the design for the person subject to protection.

Bio-Sensing Convergence Big Data Computing Architecture (바이오센싱 융합 빅데이터 컴퓨팅 아키텍처)

  • Ko, Myung-Sook;Lee, Tae-Gyu
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.2
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    • pp.43-50
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    • 2018
  • Biometric information computing is greatly influencing both a computing system and Big-data system based on the bio-information system that combines bio-signal sensors and bio-information processing. Unlike conventional data formats such as text, images, and videos, biometric information is represented by text-based values that give meaning to a bio-signal, important event moments are stored in an image format, a complex data format such as a video format is constructed for data prediction and analysis through time series analysis. Such a complex data structure may be separately requested by text, image, video format depending on characteristics of data required by individual biometric information application services, or may request complex data formats simultaneously depending on the situation. Since previous bio-information processing computing systems depend on conventional computing component, computing structure, and data processing method, they have many inefficiencies in terms of data processing performance, transmission capability, storage efficiency, and system safety. In this study, we propose an improved biosensing converged big data computing architecture to build a platform that supports biometric information processing computing effectively. The proposed architecture effectively supports data storage and transmission efficiency, computing performance, and system stability. And, it can lay the foundation for system implementation and biometric information service optimization optimized for future biometric information computing.

Performance Analysis of Implementation on IoT based Smart Wearable Mine Detection Device

  • Kim, Chi-Wook
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.12
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    • pp.51-57
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    • 2019
  • In this paper, we analyzed the performance of IoT based smart wearable mine detection device. There are various mine detection methods currently used by the military. Still, in the general field, mine detection is performed by visual detection, probe detection, detector detection, and other detection methods. The detection method by the detector is using a GPR sensor on the detector, which is possible to detect metals, but it is difficult to identify non-metals. It is hard to distinguish whether the area where the detection was performed or not. Also, there is a problem that a lot of human resources and time are wasted, and if the user does not move the sensor at a constant speed or moves too fast, it is difficult to detect landmines accurately. Therefore, we studied the smart wearable mine detection device composed of human body antenna, main microprocessor, smart glasses, body-mounted LCD monitor, wireless data transmission, belt type power supply, black box camera, which is to improve the problem of the error of mine detection using unidirectional ultrasonic sensing signal. Based on the results of this study, we will conduct an experiment to confirm the possibility of detecting underground mines based on the Internet of Things (IoT). This paper consists of an introduction, experimental environment composition, simulation analysis, and conclusion. Introduction introduces the research contents such as mines, mine detectors, and research progress. It consists of large anti-personnel mine, M16A1 fragmented anti-mine, M15 and M19 antitank mines, plastic bottles similar to mines and aluminum cans. Simulation analysis is conducted by using MATLAB to analyze the mine detection device implementation performance, generating and transmitting IoT signals, and analyzing each received signal to verify the detection performance of landmines. Then we will measure the performance through the simulation of IoT-based mine detection algorithm so that we will prove the possibility of IoT-based detection landmine.