A Data Driven Multi-Layer Framework of Pervasive Information Computing System for eHealthcare

Vivek Tiwari and Basant Tiwari
Additional contact information
Vivek Tiwari: IIIT-NR, Raipur, India
Basant Tiwari: Hawassa University Institute of Technology, Awasa, Ethiopia

International Journal of E-Health and Medical Communications (IJEHMC), 2019, vol. 10, issue 4, 66-85

Abstract: In the last decade, significant advancements in telecommunications and informatics have seen which incredibly boost mobile communications, wireless networks, and pervasive computing. It enables healthcare applications to increase human livelihood. Furthermore, it seems feasible to continuous observation of patients and elderly individuals for their wellbeing. Such pervasive arrangements enable medical experts to analyse current patient status, minimise reaction time, increase livelihood, scalability, and availability. There is found plenty of remote patient monitoring model in literature, and most of them are designed with limited scope. Most of them are lacking to give an overall unified, complete model which talk about all state-of-the-art functionalities. In this regard, remote patient monitoring systems (RPMS's) play important roles through wearable devices to monitor the patient's physiological condition. RPMS also enables the capture of related videos, images, and frames. RPMS do not mean to enable only capturing various sorts of patient-related information, but it also must facilitate analytics, transformation, security, alerts, accessibility, etc. In this view, RPMS must ensure some broad issues like, wearability, adaptability, interoperability, integration, security, and network efficiency. This article proposes a data-driven multi-layer architecture for pervasively remote patient monitoring that incorporates these issues. The system has been classified into five fundamental layers: the data acquisition layer, the data pre-processing layer, the network and data transfer layer, the data management layer and the data accessing layer. It enables patient care at real-time using the network infrastructure efficiently. A detailed discussion on various security issues have been carried out. Moreover, standard deviation-based data reduction and a machine-learning-based data access policy is also proposed.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJEHMC.2019100106 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jehmc0:v:10:y:2019:i:4:p:66-85

Access Statistics for this article

International Journal of E-Health and Medical Communications (IJEHMC) is currently edited by Joel J.P.C. Rodrigues

More articles in International Journal of E-Health and Medical Communications (IJEHMC) from IGI Global
Bibliographic data for series maintained by Journal Editor ().