Internet of medical things and healthcare 4.0: trends, requirements, challenges, and research directions
Authors:
- Manar Osama,
- Abdelhamied A. Ateya,
- Mohammed S. Sayed,
- Mohamed Hammad,
- Paweł Pławiak,
- Ahmed A. Abd El-Latif,
- Rania A. Elsayed
Abstract
Healthcare 4.0 is a recent e-health paradigm associated with the concept of Industry 4.0. It provides approaches to achieving precision medicine that delivers healthcare services based on the patient’s characteristics. Moreover, Healthcare 4.0 enables telemedicine, including telesurgery, early predictions, and diagnosis of diseases. This represents an important paradigm for modern societies, especially with the current situation of pandemics. The release of the fifth-generation cellular system (5G), the current advances in wearable device manufacturing, and the recent technologies, e.g., artificial intelligence (AI), edge computing, and the Internet of Things (IoT), are the main drivers of evolutions of Healthcare 4.0 systems. To this end, this work considers introducing recent advances, trends, and requirements of the Internet of Medical Things (IoMT) and Healthcare 4.0 systems. The ultimate requirements of such networks in the era of 5G and next-generation networks are discussed. Moreover, the design challenges and current research directions of these networks. The key enabling technologies of such systems, including AI and distributed edge computing, are discussed.
- Record ID
- CUT3ba8e805e5dd40beb65b0d3ab32fdce5
- Publication categories
- ;
- Author
- Journal series
- Sensors, ISSN , e-ISSN 1424-8220, Biweekly
- Issue year
- 2023
- Vol
- 23
- No
- 17
- Pages
- [1-36]
- Article number
- 7435
- Other elements of collation
- fot.; rys.; tab.; Bibliografia (na s.) - 31-36; Bibliografia (liczba pozycji) - 118; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - Vol. 23, Iss. 17
- Substantive notes
- This article belongs to the Special Issue: IoT in Smart Mobile Health Application
- Keywords in English
- internet of medical things, healthcare 4.0, artificial intelligence, distributed edge computing, 5G, e-health
- ASJC Classification
- ; ; ;
- DOI
- DOI:10.3390/s23177435 Opening in a new tab
- URL
- https://www.mdpi.com/1424-8220/23/17/7435 Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 100
- Score source
- journalList
- Score
- Publication indicators
- Citation count
- 22
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT3ba8e805e5dd40beb65b0d3ab32fdce5/
- URN
urn:pkr-prod:CUT3ba8e805e5dd40beb65b0d3ab32fdce5
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.