• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.76-77
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• 2018

Recently, as the quality of life of the morden people has increasingly grown, the demand for traveling to foreign countries has been rapidly increasing. However, there are not enough safety systems avaliable for international travelers. Therefore, it is necessary to provide helpful information on disaster, crimes and dangerous areas by country for travelers. In this paper, we propse a smart device-based smart security notification service system for emergent situations of overseas travelers. the proposed notification system provides information about disaster, crime and dangerous areas is designed to be provided to users.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.499-505
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• 2016

In this Paper, we propose a body-area localization technique based on WUSB (Wireless USB) over WBAN (Wireless Body Area Networks) protocol required for wearable computer systems. The proposed localization algorithm is executed on the basis of WUSB over WBAN protocol at each sensor node comprising peripherals of a wearable computer system. To increase the accuracy of input information through various body motions in wearable computer systems, a new localization technique with high precision must be developed. To achieve the goal, This paper proposes a combined TDoA/FDoA/AoA (Time Of Arrival/Time Difference Of Arrival/Angle Of Arrival) localization technique with more than four WUSB over WBAN devices to estimate body-area location accurately. The combined TDoA/FDoA/AoA technique reduces 10mm in location estimation errors comparing with a combined TDoA/FDoA technique. This performance enhancement in location error reduction can be ignored at other systems but is meaningful results in body-area localization-based communications.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.265-266
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• 2015

인간의 사고 및 행동능력은 환경부하, 작업의 내용 등 외부환경에 큰 영향을 받는다. 선박운항 시, 인간-기계시스템 환경에서 항해사의 일정한 수준 이상의 판단 및 조선능력은 안전운항을 위해 매우 중요한 요소이다. 특히 협수로 항해시, 선박통항량이 많은 해역을 항해할 경우 선교에서의 작업부하가 커지고 그로 인한 피로 및 긴장에 의한 심신 기능이 저하되어, 항해사의 조선(操船)능력에 영향을 미치게 될 것이다. 그러나 선박운항 또는 입출항 시 항해사의 생리적, 심리적 스트레스를 측정하여 계량화한 연구는 미비하다. 따라서 본 연구에서는 웨어러블 심박수 측정장치를 이용하여 항해사의 심박수 변화를 측정 분석하고, 항해사의 선박 운항작업 시 발생하는 스트레스를 계량화하여 모델을 개발하기 위한 기초연구를 수행하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1145-1147
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• 2017

사회적 소외계층이 증가함에 따라 무연고 사망자가 늘어나는 사례가 늘고 있다. 따라서 본 논문은 자체 제작한 웨어러블 디바이스를 활용하여 무연고 소외계층의 건강을 관찰 및 응급상황을 대처하고 고독사를 방지하는 서비스를 제안한다. 제안한 웨어러블 디바이스는 사용자가 착용 시 심장 박동, 온도, 습도의 생명 정보를 측정 및 저장하고, 저장된 데이터와 움직임을 감지할 PIR 센서의 움직임 데이터 값을 비교하여 응급 상황을 보여준다. 이를 위해서 사용자 용 웨어러블 디바이스, DB 관리서버 및 웹 페이지를 구축하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.428-430
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• 2018

본 논문에서는 독감확산 예측을 위한 웨어러블 센서를 이용한 기침 감지 모델을 제안한다. 서로 상이한 기침 신체데이터를 사용하고 기침 감지 알고리즘의 구현없이 기계가 학습하는 방식인 멀티모달 DNN을 이용하여 설계하였다. 또한 웨어러블 센서를 통해 실생활의 기침 오디오 데이터와 기침 3축 가속도 데이터를 수집하였고, 두 개의 데이터중 하나의 데이터만으로도 감지를 위한 학습이 가능토록하기 위해 각각 MFCC와 FFT를 이용하여 특징 벡터를 추출하는 방법을 이용하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.75-77
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• 2022

본 논문에서는 복합 개체 센싱(다축 멀티 센서)이 적용되고 수중 다이빙 시 몸통, 핀 부분의 동작 정보를 수집하여 수중 활동 시 발차기, 몸통 회전, 몸통 위치, 이동 속도 등의 움직임 정보를 수집 할 수 있도록 구성하여 다이빙 시 발생되는 다양한 동작 정보를 실시간 수집 할 수 있는 웨어러블 시스템 개발을 제안한다. 다이빙 Suit, 몸에 탈부착이 가능하도록 구성하여 개인의 수중 다이빙 상황을 실시간 정보 수집을 통하여 객관적으로 다이빙 자세, 공기소모와 의 관계 분석, 다이빙 습관 교정, 속도 조절 등 자가 진단 체계화 정보 구축하고, 다이빙 포함 다양한 해양 스포츠의 훈련 이슈는 수중에서 발생되는 문제를 객관화된 정보 없이 강사, 훈련생의 느낌으로만 교정 한다는 의미에서 보다 객관화된 센싱 정보와 복합적으로 수집 분석된 정보를 학습된 정보의 비교분석에 의하여 수중 다이빙의 문제점을 교정 할 수 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1087-1095
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• 2014

A recent major development in computer technology is the advent of the wearable computer system that is based on human-centric interface technology trends and ubiquitous computing environments. Wearable computer systems can use the wireless universal serial bus (WUSB) that refers to USB technology that is merged with WiMedia PHY/MAC technical specifications. In this paper, we focus on an integrated system of the wireless USB over the IEEE 802.15.6 wireless body area networks (WBAN) for wireless wearable computer systems supporting U-health services. And a communication structure that can differentiate QoS of U-health WBAN and WUSB traffic with different priorities is proposed for WUSB over IEEE 802.15.6 hierarchical protocol. In our proposal and performance evaluation, throughputs of U-health WBAN and WUSB traffic are analyzed under single and multiple QoS classes to evaluate the effectiveness of proposed QoS differentiating structure in WUSB over IEEE 802.15.6.

• Journal of KIISE:Software and Applications
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• v.41 no.8
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• pp.586-597
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• 2014

The next generation mobile computing technology is recently attracting attention that smartphone and wearable device imbedded with various sensors are being deployed in the world. Existing activity and posture recognition research can be divided into two different ways considering feature of one's movement. While activity recognition focuses on catching distinct pattern according to continuous movement, posture recognition focuses on sudden change of posture and body orientation. There is a lack of research constructing a system mixing two separate patterns which could be applied in real world. In this paper, we propose a method to use both smartphone and wearable device to recognize activity and posture in the same time. To use smartphone and wearable sensor data together, we designed a pre-processing method and constructed recognition model mixing signal vector magnitude and orientation pattern features of vertical and horizontal. We considered cycling, fast/slow walking and running activities, and postures such as standing, sitting, and laying down. We confirmed the performance and validity by experiment, and proved the feasibility in real world.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.1
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• pp.34-39
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• 2018

Along with the development of ICT technology, wearable devices of various sizes and shapes have been developed. In addition, performance and specifications are rebuilt with IOT fusion products so that they can connect with the current smartphone. This is one of the general-purpose technologies of the 4th industrial revolution, which is spot-lighted with technology that changes the quality and environment of our lives. Along with this, as new technology products combining health care technology increases, various functions are provided to users who need it. Wearable technology is ongoing trend of technology development. It also sells products developed as products in the form of smart watches. At present, various related products are made in various ways, and it is recommended to use the Arduino processor in accordance with the application. In this study, we developed wearable physical activity monitoring system using open source hardware based TinyDuino. TinyDuino is an ultra-compact Arduino compatible board made on the basis of Atmega process Board, and it can be programmed in open source integrated development environment(named Sketch). The physical activity monitoring system of the welfare body can be said to be a great advantage, as a smart u-Healthcare system that can perform daily health management.

• Journal of KIISE
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• v.43 no.5
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• pp.531-540
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• 2016

Development of various sensors attached to mobile and wearable devices has led to increasing recognition of current context-based service to the user. In this study, we proposed a probabilistic model for recognizing user's food intake context, which can occur in a great variety of contexts. The model uses low-level sensor data from mobile and wrist-wearable devices that can be widely available in daily life. To cope with innate complexity and fuzziness in high-level activities like food intake, a context model represents the relevant contexts systematically based on 4 components of activity theory and 5 W's, and tree-structured Bayesian network recognizes the probabilistic state. To verify the proposed method, we collected 383 minutes of data from 4 people in a week and found that the proposed method outperforms the conventional machine learning methods in accuracy (93.21%). Also, we conducted a scenario-based test and investigated the effect contribution of individual components for recognition.