Internet of Medical Things (IoMT): Overview, Taxonomies, and Classifications

Khaled, Ahmed E. (2022) Internet of Medical Things (IoMT): Overview, Taxonomies, and Classifications. Journal of Computer and Communications, 10 (08). pp. 64-89. ISSN 2327-5219

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Abstract

Recent research efforts have created rapid advances in the field of the Internet of Things (IoT) in terms of communication protocols, sensing technologies, computing capabilities, next-generation wireless technologies, big data and AI techniques, and on-device, edge, cloud processing. These advances created a paradigm shift and generated a wide range of potential opportunities for a new major field known as the Internet of Medical Things (IoMT), as well as subfields like mobile Health (mHeatlh) and digital or electronic Health (eHealth). This paper provides an overview of the Internet of Medical Things and presents a classification to define the primary users and their roles and involvement in smart healthcare systems. The paper then presents taxonomy on the deployment scales of different healthcare environments, from personal healthcare to widescale connected healthcare systems. The overview also discusses the n-tier architecture of IoMT, then presents a set of taxonomies and classifications on the different medical devices used in healthcare systems as well as non-medical devices used to provide context-aware information about the surrounding environment. The paper then concludes the overview by presenting the different healthcare-related applications and services, a comparison between traditional and smart healthcare systems, and the different obstacles and challenges in the field of IoMT to guide the development of new services and devices. Many survey papers in the literature focused on similar points; however, up to our knowledge, this is the first paper to present taxonomies and classifications for these IoMT essential topics. The presented taxonomies and classifications provide the manufacturers of medical devices and the developers of healthcare services a deeper understanding of the healthcare systems’ landscape to address different requirements and demands.

Item Type: Article
Subjects: Open Archive Press > Computer Science
Depositing User: Unnamed user with email support@openarchivepress.com
Date Deposited: 28 Apr 2023 05:25
Last Modified: 18 Mar 2024 04:32
URI: http://library.2pressrelease.co.in/id/eprint/1049

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