Open Access

ARTICLE

Ontological Model for Cohesive Smart Health Services Management

Muhammad Raza Naqvi¹, Muhammad Waseem Iqbal^2,*, Syed Khuram Shahzad³, M. Usman Ashraf⁴, Khalid Alsubhi⁵, Hani Moaiteq Aljahdali⁶

1 Le Laboratoire Génie de Production de l’École Nationale d’Ingénieurs de Tarbes (LGP-INP-ENIT), Université de Toulouse, CEDEX, Tarbes, 65016, France
2 Department of Software Engineering, Superior University, Lahore, 53700, Pakistan
3 Department of Informatics & Systems, University of Management & Technology, Lahore, 54000, Pakistan
4 Department of Computer Science, University of Management and Technology, Sialkot, 51310, Pakistan
5 Department of Computer Science, King Abdul-Aziz University, Jeddah, 21577, Saudi Arabia
6 Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, 21577, Saudi Arabia

* Corresponding Author: Muhammad Waseem Iqbal. Email:

Computers, Materials & Continua 2023, 74(2), 3679-3695. https://doi.org/10.32604/cmc.2023.030340

Received 24 March 2022; Accepted 29 May 2022; Issue published 31 October 2022

Abstract

Health care has become an essential social-economic concern for all stakeholders (e.g., patients, doctors, hospitals etc.), health needs, private care and the elderly class of society. The massive increase in the usage of health care Internet of things (IoT) applications has great technological evolvement in human life. There are various smart health care services like remote patient monitoring, diagnostic, disease-specific remote treatments and telemedicine. These applications are available in a split fashion and provide solutions for variant diseases, medical resources and remote service management. The main objective of this research is to provide a management platform where all these services work as a single unit to facilitate the users. The ontological model of integrated healthcare services is proposed by getting requirements from various existing healthcare services. There were 26 smart health care services and 26 smart health care services to classify the knowledge-based ontological model. The proposed ontological model is derived from different classes, relationships, and constraints to integrate health care services. This model is developed using Protégé based on each interrelated/correlated health care service having different values. Semantic querying SPARQL protocol and RDF query language (SPARQL) were used for knowledge acquisition. The Pellet Reasoner is used to check the validity and relations coherency of the proposed ontology model. Comparative to other smart health care services integration systems, the proposed ontological model provides more cohesiveness.

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Keywords

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