A Workload Characterization for the Internet of Medical Things (IoMT)

Limaye, Ankur; Adegbija, Tosiron

doi:10.1109/isvlsi.2017.60

Cited by 18 publications

(7 citation statements)

References 15 publications

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“…Thus, the Fog-based storage strategies have to cope with this limitation. Besides, the analyzed works mention the performance related to the manipulation of information in the applications as the main reason to use Fog Computing in the health field [10,15,[20][21][22][23][24][25][26].…”

Section: Related Workmentioning

confidence: 99%

A Fog Computing-Based Architecture for Medical Records Management

Silva

Aquino

Melo

et al. 2019

Wireless Communications and Mobile Computing

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The aging of the world’s population and the growth in the number of people with chronic diseases have increased expenses with medical care. Thus, the use of technological solutions has been widely adopted in the medical field to improve the patients’ health. In this context, approaches based on Cloud Computing have been used to store and process the information generated in these solutions. However, using Cloud can create delays that are intolerable for medical applications. Thus, the Fog Computing paradigm emerged as an alternative to overcome this problem, bringing computation and storage closer to the data sources. However, managing medical data stored in Fog is still a challenge. Moreover, characteristics of availability, performance, interoperability, and privacy need to be considered in approaches that aim to explore this problem. So, this article shows a software architecture based on Fog Computing and designed to facilitate the management of medical records. This architecture uses Blockchain concepts to provide the necessary privacy features and to allow Fog Nodes to carry out the authorization process in a distributed way. Finally, this paper describes a case study that evaluates the performance, privacy, and interoperability requirements of the proposed architecture in a home-centered healthcare scenario.

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Section: Related Workmentioning

confidence: 99%

A Fog Computing-Based Architecture for Medical Records Management

Silva

Aquino

Melo

et al. 2019

Wireless Communications and Mobile Computing

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“…Internet of Things (IoT) is widely applied in many fields, most notably in healthcare (15,16). Applied IoT in the medical field is called the Internet of Medical Things (IoMT) (17). The smartphone application (App) used in our research performs the function of IoMT, which makes it easier to collect and manage health data.…”

Section: Introductionmentioning

confidence: 99%

Behavioral Intention to Use a Smartphone Usage Management Application Between a Non-Problematic Smartphone Use Group and a Problematic Use Group

Choi

Lee

et al. 2021

Front. Psychiatry

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Despite the many advantages of smartphone in daily life, there are significant concerns regarding their problematic use. Therefore, several smartphone usage management applications have been developed to prevent problematic smartphone use. The purpose of this study is to investigate the factors of users' behavioral intention to use smartphone usage management applications. Participants were divided into a smartphone use control group and a problematic use group to find significant intergroup path differences. The research model of this study is fundamentally based on the Technology Acceptance Model and Expectation-Confirmation Theory. Based on this theorem, models were modified to best suit the case of problematic smartphone use intervention by smartphone application. We conducted online surveys on 511 randomly selected smartphone users aged 20–60 in South Korea, in 2018. The Smartphone Addiction Proneness Scale was used to measure participants' smartphone dependency. Descriptive statistics were used for the demographic analysis and collected data were analyzed using IBM SPSS Statistics 24.0 and Amos 24.0. We found that in both non-problematic smartphone use group and problematic smartphone use group, facilitating factors and perceived security positively affect the intentions of users to use the application. One distinct difference between the groups was that the latter attributed a lower importance to perceived security than the former. Some of our highlighted unique points are envisioned to provide intensive insights for broadening knowledge about technology acceptance in the field of e-Addictology.

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“…Limaye and Adegbija [78] provided a comprehensive review of medical applications and algorithms in IoMT architectures and their integration with edge computing. IoMT workloads were compared using MiBench, an existing open source embedded system benchmark suite.…”

Section: Edge-and Cloud-based Smart Health Carementioning

confidence: 99%