• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2377-2397
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• 2020

Human activity recognition is widely used in smart homes, health care and indoor monitor. Traditional approaches all need hardware installation or wearable sensors, which incurs additional costs and imposes many restrictions on usage. Therefore, this paper presents a novel device-free activities recognition system based on the advanced wireless technologies. The fine-grained information channel state information (CSI) in the wireless channel is employed as the indicator of human activities. To improve accuracy, both amplitude and phase information of CSI are extracted and shaped into feature vectors for activities recognition. In addition, we discuss the classification accuracy of different features and select the most stable features for feature matrix. Our experimental evaluation in two laboratories of different size demonstrates that the proposed scheme can achieve an average accuracy over 95% and 90% in different scenarios.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.246-252
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• 2018

Hand gestures are attracting attention as a NUI (Natural User Interface) of wearable devices such as smart glasses. Recently, to support efficient media consumption in IoT (Internet of Things) and wearable environments, the standardization of IoMT (Internet of Media Things) is in the progress in MPEG. In IoMT, it is assumed that hand gesture detection and recognition are performed on a separate device, and thus provides an interoperable interface between these modules. Meanwhile, deep learning based hand gesture recognition techniques have been recently actively studied to improve the recognition performance. In this paper, we propose a method of hand gesture recognition based on CNN (Convolutional Neural Network) for various applications such as media consumption in wearable devices which is one of the use cases of IoMT. The proposed method detects hand contour from stereo images acquisitioned by smart glasses using depth information and color information, constructs data sets to learn CNN, and then recognizes gestures from input hand contour images. Experimental results show that the proposed method achieves the average 95% hand gesture recognition rate.

• Journal of Navigation and Port Research
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• v.44 no.6
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• pp.557-563
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• 2020

Digital Twin Technology is currently being utilized in many industries and logistics seems soon to follow that trend. Currently, technology introduction to container terminals is restrictedly developing. In reviewing the existing literature, it became clear that research on the application of Digital Twin technology for container terminals is deficient. This study fulfilled AHP and IPA analysis causing fields to adjust priority at the container terminal. The result of analysis on the urgent necessity of adjustable fields' detailed elements from Digital Twin Technology, ATC, intelligent CCTV, and container yards, and showed that they were of the highest priority level. Also, VR/AR Equipment, AYT, Smart Container, Automated Container Delivery Facility, Refrigerated/Freezer Container, Wearable Device for Port Maintenance, and Smart Buoy were reviewed in detail. Our group suggests AQC, Berth, AGV, ASC, Apron, and Automated Mooring as potentially useful Digital Twin Technologies. Finally, our research suggests the OSS equipment, intermodal linkage facility, intelligent drone, and hazardous material storage are areas of low priority.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.32-42
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• 2024

The Internet of Things (IoT) is set to transform patient care by enhancing data collection, analysis, and management through medical sensors and wearable devices. However, the convergence of IoT device vulnerabilities and the sensitivity of healthcare data raises significant data integrity and privacy concerns. In response, this research introduces the Smart-Coord system, a practical and affordable solution for securing healthcare IoT. Smart-Coord leverages blockchain technology and coordinate-based access management to fortify healthcare IoT. It employs IPFS for immutable data storage and intelligent Solidity Ethereum contracts for data integrity and confidentiality, creating a hierarchical, AES-CBC-secured data transmission protocol from IoT devices to blockchain repositories. Our technique uses a unique coordinate system to embed confidentiality and integrity regulations into a single access control model, dictating data access and transfer based on subject-object pairings in a coordinate plane. This dual enforcement technique governs and secures the flow of healthcare IoT information. With its implementation on the Matic network, the Smart-Coord system's computational efficiency and cost-effectiveness are unparalleled. Smart-Coord boasts significantly lower transaction costs and data operation processing times than other blockchain networks, making it a practical and affordable solution. Smart-Coord holds the promise of enhancing IoT-based healthcare system security by managing sensitive health data in a scalable, efficient, and secure manner. The Smart-Coord framework heralds a new era in healthcare IoT adoption, expertly managing data integrity, confidentiality, and accessibility to ensure a secure, reliable digital environment for patient data management.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.37-46
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• 2015

Nowadays, given the popularity of wearable devices, The smartwatch is considered as the leading product category and taking the main share of wearable device market. So far smartwatch is only used as an accessorial device of smart phones due to its screen size. The objective of this study is to review literatures and find solutions to overcome the screen limitations. In the literature review, several methods are introduced including using other devices as output devices, other object as screens by projecting technologies, and enlarging screen size by flexible display. Based on that, possible solutions including seamless display and user-centered interaction methods were investigated. Future research directions were also introduced at the end of this study.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.18-26
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• 2015

Measuring the heart rate during exercise is important to properly control the amount of exercise. With the recent advent of smart device usage, there is a dramatic increase in interest in devices for the real-time measurement of the heart rate during exercise. During intensive exercise, accurate heart rate estimation from wrist-type photoplethysmography (PPG) signals is a very difficult problem due to motion artifact (MA). In this study, we propose an efficient algorithm for an accurate estimation of the heart rate from wrist-type PPG signals. For the twelve data sets, the proposed algorithm achieves the average absolute error of 1.38 beat per minute (BPM) and the Pearson correlation between the estimates and the ground-truth of heart rate was 0.9922. The proposed algorithm presents the strengths in an accurate estimation together with a fast computation speed, which is attractive in application to wearable devices.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1345-1352
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• 2023

With the development of virtual reality (VR) and blockchain technology, Metaverse is being used in various fields such as games, education, and social networking. At the same time, shipments of wearable devices such as smartwatches are growing every year, becoming more and more integrated into people's daily lives. This study presents a new possibility of reflecting the user's body signals measured through the combination of the two phenomena in the metaverse character. Various biometric information such as the user's heart rate and amount of exercise collected through the smartwatch are reflected on the character in the metaverse, allowing the user's physical condition to be reflected in the virtual world. Through this, Metaverse is expected to provide a new experience that can be called 'extended reality' beyond simple virtual reality, improve user's satisfaction with Metaverse, and suggest a direction for the development of smartwatches.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.3
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• pp.225-232
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• 2015

The smart watch is the most popular wearable computing device because it takes a form of wristwatch. Many smart watches have adopted the touch screen interface due to the limited size of display. This paper focuses on touch key size and spacing that affect the usability about the touch key of smart watch. The experiments were made for four touch key sizes (width${\times}$height; $5{\times}5$, $5{\times}7$, $7{\times}5$, $7{\times}7mm$) and nine touch key spacing (vertical${\times}$horizontal; $0{\times}0$, $0{\times}1$, $0{\times}3$, $1{\times}0$, $1{\times}1$, $1{\times}3$, $3{\times}0$, $3{\times}1$, $3{\times}3mm$). The completion time, error rate, control discomfort and identification discomfort were measured. The touch key size $7{\times}7$, $7{\times}5$ and the touch key spacing $3{\times}3$, $1{\times}3$ provided the best results in terms of the completion time and the control discomfort, while the square touch key ($7{\times}7$, $5{\times}5$) provided the best performance for the error rate measure. The result of this study can help ergonomically design the touch interface of the smart watch.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.2
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• pp.129-132
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• 2017

A conventional pulse oximeter has high power consumption; thus, its mobility is severely limited. In this paper, we discuss the drawbacks of the existing pulse oximeters and propose a new ultra-low-power pulse oximeter that supports wireless data transmission for remotely monitoring vital signs, such as peripheral capillary oxygen saturation (SpO2) and beats per minute (BPM). We could notably reduce power consumption by using a low-frequency single clock in all well-customized modules. Also, our device is publicly certified, and thus, possibly engaged in clinical trials for commercial use.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.107-114
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• 2018

Recently, various wearable personal devices such as a smart watch have been developed and these personal devices are being miniaturized. The user desires to receive new services from personal devices as well as services that have been received from personal computers, anytime and anywhere. However, miniaturization of devices involves constraints on resources such as limited input and output and insufficient power. In order to solve these resource constraints, this paper proposes a resource collaboration system which provides a service by composing sharable resources in the resource sharing environment like IoT. the paper also propose a method to infer and recommend user-customized resources among various sharable resources. For this purpose, the paper defines an ontology for resource inference. This paper also classifies users behavior types based on a user model and then uses them for resource recommendation. The paper implements the proposed method as a prototype system on a personal device with limited resources developed for resource collaboration and shows the effectiveness of the proposed method by evaluating user satisfaction.