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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
