Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/1528
Title: Exploitation of Emerging Technologies and Advanced Networks for a Smart Healthcare System
Authors: Minopoulos, Georgios
Memos, Vasileios A.
Stergiou, Christos
Stergiou, Konstantinos D.
Plageras, Andreas P.
Koidou, Maria P.
Psannis, Kostas E.
Type: Article
Subjects: FRASCATI::Engineering and technology
Keywords: advanced networks
emerging technologies
medical sector
smart healthcare
Issue Date: 2022
Publisher: MDPI
Source: Applied Sciences
Volume: 12
Issue: 12
First Page: 5859
Volume Title: Application of Data Analytics in Smart Healthcare
Abstract: Current medical methods still confront numerous limitations and barriers to detect and fight against illnesses and disorders. The introduction of emerging technologies in the healthcare industry is anticipated to enable novel medical techniques for an efficient and effective smart healthcare system. Internet of Things (IoT),Wireless Sensor Networks (WSN), Big Data Analytics (BDA), and Cloud Computing (CC) can play a vital role in the instant detection of illnesses, diseases, viruses, or disorders. Complicated techniques such as Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) could provide acceleration in drug and antibiotics discovery. Moreover, the integration of visualization techniques such as Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) with Tactile Internet (TI), can be applied from the medical staff to provide the most accurate diagnosis and treatment for the patients. A novel system architecture, which combines several future technologies, is proposed in this paper. The objective is to describe the integration of a mixture of emerging technologies in assistance with advanced networks to provide a smart healthcare system that may be established in hospitals or medical centers. Such a system will be able to deliver immediate and accurate data to the medical stuff in order to aim them in order to provide precise patient diagnosis and treatment.
URI: https://doi.org/10.3390/app12125859
https://ruomo.lib.uom.gr/handle/7000/1528
ISSN: 2076-3417
Other Identifiers: 10.3390/app12125859
Appears in Collections:Department of Applied Informatics

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