Reliable service delivery in Tele-health care systems. (1st August 2018)

• Record Type: Journal Article
• Authors: Rawashdeh, Majdi; AL Zamil, Mohammed GH.; Hossain, M. Shamim; Samarah, Samer; Amin, Syed Umar; Muhammad, Ghulam
• Is Part Of: Journal of network and computer applications. Volume 115(2018)
• Page Start: 86
• Page End: 93
• Publication Date: 2018-08-01
• Subjects: Tele-health -- IoT -- Cloud computing -- Network applications -- Data mining; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2018.04.015
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: Modern ICT Applications on Tele-health focuses on providing the smart infrastructure that facilitates the delivery of health services. While Internet-of-Things (IoT) and cloud-computing platforms assist the implementation of such architecture, the reliability of service delivery during network disconnection is still an open issue in this domain. This paper proposes a prediction methodology that is able to deliver reliable services with acceptable accuracy by incorporating domain-specific knowledge into exchanged data. The proposed service will be of a great value in a situation where the network availability is not reliable. The contributions of this work are to 1) measure the impact of ontology enrichment on classifying the health data, 2) develop a prediction model that is able to predict patients' readings with an acceptable accuracy, and 3) minimize communicating messages among the network components. Three experiments have been conducted on a real health dataset to measure the performance of the proposed methodology. The results showed that our proposed methodology improved the reliability of the Tele-health services implemented on the top of IoT and cloud-computing platforms. Highlights: Tele-healthcare systems require reliable service delivery paradigm to deliver quality services. A solution at Data-Layer provides efficient and effective solution. Ontology enriched prediction model that is based on Hidden Markov Model. The performance measures efficiency in terms of accuracy, sensitivity, and communication load.