Open Access

ARTICLE

A Process Oriented Integration Model for Smart Health Services

Farzana Kausar Gondal^1,*, Syed Khuram Shahzad², Muhammad Arfan Jaffar³, Muhammad Waseem Iqbal⁴

1 Department of Computer Science, Superior University, Lahore, 54600, Pakistan
2 Department of Informatics and Systems, University of Management and Technology, Lahore, 54000, Pakistan
3 Faculty of Computer Science & IT, Superior University, Lahore, 54600, Pakistan
4 Department of Software Engineering, Superior University, Lahore, 54600, Pakistan

* Corresponding Author: Farzana Kausar Gondal. Email:

Intelligent Automation & Soft Computing 2023, 35(2), 1369-1386. https://doi.org/10.32604/iasc.2023.028407

Received 09 February 2022; Accepted 15 March 2022; Issue published 19 July 2022

Abstract

Cities are facing challenges of high rise in population number and consequently need to be equipped with latest smart services to provide luxuries of life to its residents. Smart integrated solutions are also a need to deal with the social and environmental challenges, caused by increasing urbanization. Currently, the development of smart services’ integrated network, within a city, is facing the barriers including; less efficient collection and sharing of data, along with inadequate collaboration of software and hardware. Aiming to resolve these issues, this paper recommended a solution for a synchronous functionality in the smart services’ integration process through modeling technique. Using this integration modeling solution, at first, the service participants, processes and tasks of smart services are identified and then standard illustrations are developed for the better understanding of the integrated service group environment. Business process modeling and notation (BPMN) language based models are developed and discussed for a devised case study, to test and experiment i.e., for remote healthcare from a smart home. The research is concluded with the integration process model application for the required data sharing among different service groups. The outcomes of the modeling are better understanding and attaining maximum automation that can be referenced and replicated.

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Keywords

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