• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.331-333
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• 2016

정보기술을 적용한 다양한 웨어러블 기기들이 출시되고 있지만 일부 제품군만 시장이 형성되고 있는데, 일반 소비자들이 일상적으로 사용하기 시작한 상품군은 스마트워치라고 할 수 있다. 본 연구에서는 시장형성 초기에 있는 스마트워치를 대상으로 소비자들의 개인적 특성 측면에서 제품이 채택되는 요인을 찾고자 하였다. 스마트워치는 아직 시장이 형성되어 있지 않고 스마트폰에 연동되어 사용되는 부가기기의 성격이 강하지만 그 자체로 가치를 인정받을 수 있어야 시장을 형성할 수 있을 것이다. 본 연구는 소비자 개인 차원에서 스마트워치가 호감도를 형성하고 사용의도를 갖게 되는 구조를 파악하였다. 본 연구는 스마트워치가 시장에서 확산되는 요인을 소비자의 개인특성 측면에서 파악했다는데서 의의가 있다. 연구결과는 아직 소비자들이 사용하지 않는 스마트워치를 비롯한 웨어러블 기기에 대한 시장 전략을 수립하는데 유용한 시사점을 제공한다고 할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.551-554
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• 2015

본 논문에서는 스마트워치의 3축 가속도 센서와 스마트폰의 기압센서를 이용한 행동 인식 시스템을 제안한다. 스마트워치에서 획득한 3축 가속도 값을 수직, 수평 성분으로 추출하고, 스마트폰에서 획득한 기압센서의 차이를 추출하여 행동을 인식하였다. 실험 결과에서 3축 가속도 센서 기반의 행동 인식률은 66.62%를 보였으나 제안한 3축 가속도 센서와 기압센서를 이용한 행동인식률은 95.45%를 보였다.

• Asian Journal for Public Opinion Research
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• v.7 no.3
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• pp.143-168
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• 2019

With much attention being paid to the rapid growth of wrist-worn smart devices, this study aimed to examine the micro-processes that determine an individual's adoption of smart bands and smartwatches. Primarily relying on the theoretical background of the extended technology acceptance model (TAM II), this study explored relationships between three groups of predictors-social, personal, and device-oriented-and the three main components of the original TAM: perceived usefulness (PU), perceived ease of use (PEOU), and behavioral intention (BI). Results from the path analysis indicated multiple factors played significant roles in increasing the PU, PEOU, and BI of wristworn smart devices: subjective norms, social image, self-efficacy, perceived service diversity, and perceived reasonable cost. The main findings from this research contribute to significantly improving the understanding of the main factors leading people to adopt wrist-worn smart devices.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.159-166
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• 2019

Recently, the advanced development of smart devices has increased the interest in health-care, and many people are paying more attentions to disease prevention than disease treatment. Among these prevention methods, the bare body movement has received much attention, and especially walking exercise is attracting much attention because it is enjoyable without any restrictions on place and time. Walking exercise is generally divided into two types: walking on the ground and climbing the stairs. Walking up the stairs consumes much more calories compared to walking on the ground. These walking exercises have the advantage that they can be easily performed by male and female without special equipments or economic considerations. However, there is a lack of applications and systems that accurately determine such walking and stair walking and measure momentum according to stair walking. In this paper, we designed and implemented a real-time walking status analysis system using smartwatch's, pedometer, smartphone's barometer and beacons.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.221-228
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• 2021

Recent improvements on the quality, fidelity and availability of biometric data have led to effective human physical activity detection (HPAD) in real time which adds significant value to applications such as human behavior identification, healthcare monitoring, and user authentication. Current approaches usually use machine-learning techniques for human physical activity recognition based on the data collected from wearable accelerometer sensor from a single wearable smart device on the user. However, collecting data from a single wearable smart device may not provide the complete user activity data as it is usually attached to only single part of the user's body. In addition, in case of the absence of the single sensor, then no data can be collected. Hence, in this paper, a continuous HPAD will be presented to effectively perform user activity detection with mobile service infrastructure using multiple wearable smart devices, namely smartphone and smartwatch placed in various locations on user's body for more accurate HPAD. A case study on a comprehensive dataset of classified human physical activities with our HAPD approach shows substantial improvement in HPAD accuracy.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.206-207
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• 2023

최근 스마트워치는 통화, 문자, 간편 결제, 기타 장치 제어 등 스마트폰의 소형화 및 경량화 형태로 연구되어 여러 서비스를 제공하고 있다. 스마트워치는 스마트폰 대비 작은 물리적 크기로 인해 적용 가능한 하드웨어의 성능이 상대적으로 낮으며, 이로 인해 낮은 수준의 보안 기능을 제공한다. 이는 스마트워치 대상 보안위협으로 이어질 수 있으며, 이에 대응하기 위한 보안위협 분석 및 도출 연구가 필요한 실정이다. 따라서, 본 논문에서는 스마트워치의 하드웨어 적용 한계점으로 인한 스마트워치와 스마트폰의 성능 차이를 분석하고, 이로 인해 발생 가능한 보안위협을 도출한다.

• Journal of Venture Innovation
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• v.6 no.3
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• pp.73-93
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• 2023

This study provides a prospect for the fast growing the smartwatch market by investigating the relationship between the satisfaction and the continuous use intention of Apple watch users, as well as the factors influencing their satisfaction. Based on the TAM, this study uses system quality, information quality, and self-efficacy as independent variables, perceived usefulness, perceived ease of use, and satisfaction as mediators, and continuous use intention as the dependent variable. We analyze the data of 256 individuals who completed an online survey with SPSS 26.0 and AMOS 26.0 software. This study conducts several tests and analyses to empirically evaluate the data including reliability analysis, factor analysis, feasibility analysis, path analysis, hypothesis verification, and mediation analysis. Our results investigate which factors may influence consumers' intention to continuously using Apple Watch devices in the future. In summary, satisfaction has a positive effect on the intention to continuously use smartwatchs. Perceived usefulness and perceived ease of use have a positive effect on satisfaction. Among the three factors (system quality, information quality, and self-efficacy), only self-efficacy has no significant impact on perceived usefulness but had a positive effect on perceived ease of use. In addition, system quality and information quality positively affect perceived usefulness, perceived ease of use, satisfaction, and continuous intention to use an Apple Watch. Taking the Apple Watch as the subject of our research topic, this study provides theoretical value by exploring the impact of user's satisfaction with their smartwatch on their continuous usage intention. This study further explains the influence of system quality, information quality, and self-efficacy on user satisfaction. Additionally, this research offers valuable insight to practitioners by confirming that information quality, system quality, and self-efficacy are important features for enhancing satisfactory user experiences which in turn may increase users' intention to continued using smartwatches.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.2
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• pp.99-111
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• 2017

Although smartwatches are different from smartphones in shape and carried method, they are also highly relevant to smartphones and have similar characteristics. This paper studied the impact of using smartphones on the intention to use smartwatches from the perspective of brand extension. The hypotheses were that the major factors of the attitude formed in the process of using smartphones affect the intention of using them and affect the trust of smartwatches. As a result of testing the hypotheses, trust in smartphonees affected trust in smartwatches. And the intention to use smartphones and the trust of smartwatches affected the intention to use smartwatches. However, the satisfaction, familiarity, and favorability of smartphones did not affect the trust of smartwatches. Smartwatches were associated with smartphones but they had independent characters. Based on the results of the study, the trust of smartwatches is very important, so the corporate managers need to find ways to improve their trust. And they should find strategies to improve the value of the product by finding out the factors that can increase the intention of using smartwatches.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.9-16
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• 2021

This study aims to develop a human activity recognition (HAR) system as a Deep-Learning (DL) classification model, distinguishing various human activities. We solely rely on the signals from a wristband accelerometer worn by a person for the user's convenience. 3-axis sequential acceleration signal data are gathered within a predefined time-window-slice, and they are used as input to the classification system. We are particularly interested in developing a Deep-Learning model that can outperform conventional machine learning classification performance. A total of 13 activities based on the laboratory experiments' data are used for the initial performance comparison. We have improved classification performance using the Convolutional Neural Network (CNN) combined with an auto-encoder feature reduction and parameter tuning. With various publically available HAR datasets, we could also achieve significant improvement in HAR classification. Our CNN model is also compared against Recurrent-Neural-Network(RNN) with Long Short-Term Memory(LSTM) to demonstrate its superiority. Noticeably, our model could distinguish both general activities and near-identical activities such as sitting down on the chair and floor, with almost perfect classification accuracy.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.385-392
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• 2022

As energy-saving techniques based on human behavior patterns have recently become an issue, the occupant-centered control system is adopted for estimating personal preference of indoor environment and optimizing environmental comfort and energy consumption. Accordingly, IoT devices have been used to collect indoor environmental quality (IEQ) data and personal data. However, the need to safely collect and manage data has been emerged due to cybersecurity issues. Therefore, this paper aims to present a framework that can safely transmit occupant-centered data collected from IoT to a private blockchain server using Hyperledger fabric. In the case study, the minimum value product of the mobile application and smartwatch application was developed to evaluate the usability of the proposed blockchain-based occupant-centered data collection framework. The results showed that the proposed framework could collect data safely and hassle-free in the daily life of occupants. In addition, the performance of the blockchain server was evaluated in terms of latency and throughput when ten people in a single office participated in the proposed data collection framework. Future works will further apply the proposed data collection framework to the building management system to automatically collect occupant data and be used in the HVAC system to reduce building energy consumption without security issues.