• Journal of Digital Convergence
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• v.14 no.3
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• pp.261-267
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• 2016

As IoT technology has gained the attention all around the world, the development for various services of healthcare, smart city, agriculture, and defense based on IoT is in progress. However, it is likely that healthcare services based on IoT have a problem of being leaked of patients' biological information by a third party and that risks patients' lives. In this paper, an IoT health care service managing model based on location sensor is proposed, which secures the biological information of a patient and simplifies the procedure to process the treatment and administration steps by using the data resources sensed. Even when an emergency occurs, this proposed model can respond quickly using the location information of the patient, which enables the staff in the hospital to locate the patient in real time. In addition, there is an advantage to minimize the time and the process of care, because the location of the equipment for necessary treatment is possible to be instantaneously located with attached sensors.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.341-349
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• 2020

The purpose of this study was conducted to explain the intention of use of IoT (internet of things) healthcare service for elderly using TAM (Technology Acceptance Model). The exogenous variables were professional support, personalization, interaction, and convenience, The endogenous variables were usefulness and intention. Data were collected from 220 elderly residents aged 65 over in welfare center and were analyzed using structural equation modeling using AMOS 25.0. The result of this study showed that professional support and personalization did not significantly difference perceived usefulness, and there were significant differences interaction, and convenience. Futhermore, perceived usefulness influence intention of use of IoT healthcare service for elderly. IoT health care service for elderly is affected by perceived usefulness. This study systematically verified the elderly's intention of using IoT-based smart healthcare services. The result of this study would be able to be used as basic data for preparing strategies to enhance their intention to use the services.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.371-375
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• 2018

Objectives: To successfully introduce an Internet of Things (IoT) system in the hospital environment, this study aimed to identify issues that should be considered while implementing an IoT based on a user demand survey and practical experiences in implementing IoT environment monitoring systems. Methods: In a field test, two types of IoT monitoring systems (on-premises and cloud) were used in Department of Laboratory Medicine and tested for approximately 10 months from June 16, 2016 to April 30, 2017. Information was collected regarding the issues that arose during the implementation process. Results: A total of five issues were identified: sensing and measuring, transmission method, power supply, sensor module shape, and accessibility. Conclusions: It is expected that, with sufficient consideration of the various issues derived from this study, IoT monitoring systems can be applied to other areas, such as device interconnection, remote patient monitoring, and equipment/environmental monitoring.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.59-67
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• 2023

The healthcare industry continues to adopt and integrate smart technology in its operations, from medical devices to managing operations. However, the adoption curve has not been smooth, and the historical record of technology adoption in the Kingdom of Saudi Arabia reveals the existence of both known and unknown issues. This review paper is aimed to explain the influences and barriers present in the Saudi healthcare sector affecting IoT technology adoption. A comprehensive discussion of the literature illustrated that Vision 2030, the privatisation trend, transformation in disease patterns and ageing, issues in management and increasing public awareness are the key drivers that may influence the need for the medical Internet of Things (mIoT) in Saudi healthcare. However, based on the past trend, the introduction and adoption of mIoT will likely experience issues such as noncompliance from doctors and nurses due to negative beliefs, lack of knowledge and inadequate perception of effort requirements. Thus, in-depth research of the factors associated with mIoT technology adoption is suggested for a smooth transition.

• Journal of Engineering Education Research
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• v.21 no.3
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• pp.66-75
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• 2018

This paper is the second part of the January 2018 issue of the Korean Society for Engineering Education, The "Equilibrium and Unbalance Analysis of Taegeuk Pattern DNA Matrix Codes," and is an extension of the paper published in the IoT Section of the 2017 Summer Conference in Jeju. In this paper, we have reviewed the history of what is life, and 5G Mobile communication: with IoT followed by recent research on influenza RNA gene mutation and DNA mutation variants, and the insights of Watson and Crick. Inspired by a single Franklin DNA X-ray diffraction photograph, they received the Nobel Prize for the Nature publication of DNA that has three patterns and regular repeatability. Professor MoonHo Lee has solved the three patterns in Diagonal, Left to Right, and Vertical matrices in a 2x2 matrix[CU; AG] and A = T = U = 30% C = G = 20%. We also proposed DNA Watch. This is the Healthcare IoT, which is seen by the DNA Watch on the wrist, the type of Tai Chi pattern of the body, and is immediately connected to the smartphone and delivered to the doctor.

• Journal of Digital Policy
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• v.1 no.1
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• pp.15-20
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• 2022

Recently, the healthcare field is trying to develop a model that can improve service quality by reflecting the requirements of various industrial fields. In this paper, we propose an Internet of Behavior (IoB) environment model that can process users' healthcare information in real time in a 5G environment to improve healthcare services. The purpose of the proposed model is to analyze the user's healthcare information through deep learning and then check the health status in real time. In this case, the biometric information of the user is transmitted through communication equipment attached to the portable medical equipment, and user authentication is performed through information previously input to the attached IoB device. The difference from the existing IoT healthcare service is that it analyzes the user's habits and behavior patterns and converts them into digital data, and it can induce user-specific behaviors to improve the user's healthcare service based on the collected data.

• Journal of Software Engineering Society
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• v.27 no.1
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• pp.15-17
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• 2018

Fast response to livestock disease and raising the reproductive success rate contribute to the improvement of farm productivity and profit margins. Due to the decrease in farm workforce and aging population, efficient livestock healthcare and breeding management are needed. In this study, we developed a mobile application for livestock healthcare and breeding management based on the collected body temperature data by IoT sensors. In case of livestock health problem, users are notified immediately via a mobile application warning message. It also provides users with a livestock breeding date function, allowing them to respond without missing the breeding season.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.35-57
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• 2021

Fog computing aims to provide the solution of bandwidth, network latency and energy consumption problems of cloud computing. Likewise, management of data generated by healthcare IoT devices is one of the significant applications of fog computing. Huge amount of data is being generated by healthcare IoT devices and such types of data is required to be managed efficiently, with low latency, without failure, and with minimum energy consumption and low cost. Failures of task or node can cause more latency, maximum energy consumption and high cost. Thus, a failure free, cost efficient, and energy aware management and scheduling scheme for data generated by healthcare IoT devices not only improves the performance of the system but also saves the precious lives of patients because of due to minimum latency and provision of fault tolerance. Therefore, to address all such challenges with regard to data management and fault tolerance, we have presented a Fault Tolerant Data management (FTDM) scheme for healthcare IoT in fog computing. In FTDM, the data generated by healthcare IoT devices is efficiently organized and managed through well-defined components and steps. A two way fault-tolerant mechanism i.e., task-based fault-tolerance and node-based fault-tolerance, is provided in FTDM through which failure of tasks and nodes are managed. The paper considers energy consumption, execution cost, network usage, latency, and execution time as performance evaluation parameters. The simulation results show significantly improvements which are performed using iFogSim. Further, the simulation results show that the proposed FTDM strategy reduces energy consumption 3.97%, execution cost 5.09%, network usage 25.88%, latency 44.15% and execution time 48.89% as compared with existing Greedy Knapsack Scheduling (GKS) strategy. Moreover, it is worthwhile to mention that sometimes the patients are required to be treated remotely due to non-availability of facilities or due to some infectious diseases such as COVID-19. Thus, in such circumstances, the proposed strategy is significantly efficient.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.981-984
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• 2015

IoT is network evolved one more step than Mobile or Internet based on the existing wire communication and can interconnect all people, things, and virtual space at any time, anywhere. In particular, Internet of Things technology is expected to be converged on medical service such as elderly home care, chronic disease management, and treatment, and then it also contributes to savings and service quality of in the medical field and leads the paradigm or innovation of healthcare industry. In this study, we analyzed the IoT technology and application cases of medical service based on the IoT at home and abroad.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1238-1249
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• 2020

Throughout the world, aging populations and doctor shortages have helped drive the increasing demand for smart healthcare systems. Recently, these systems have benefited from the evolution of the Internet of Things (IoT), big data, and machine learning. However, these advances result in the generation of large amounts of data, making healthcare data analysis a major issue. These data have a number of complex properties such as high-dimensionality, irregularity, and sparsity, which makes efficient processing difficult to implement. These challenges are met by big data analytics. In this paper, we propose an innovative analytic framework for big healthcare data that are collected either from IoT wearable devices or from archived patient medical images. The proposed method would efficiently address the data heterogeneity problem using middleware between heterogeneous data sources and MapReduce Hadoop clusters. Furthermore, the proposed framework enables the use of both fog computing and cloud platforms to handle the problems faced through online and offline data processing, data storage, and data classification. Additionally, it guarantees robust and secure knowledge of patient medical data.