Towards An Uncertain Integration and Composition Approach of Data from Heterogeneous WoT Health Services

Soura Boulaares¹*, Salma Sassi², Djamal Benslimane³ and Sami Faiz^4
1National School for Computer Science,Manouba, Tunisia
²Faculty of law, Economic,and Management Sciences,Jendouba, Tunisia
³Claude Bernard Lyon 1 University,Lyon, France
⁴Higher Institute of Multimedia Arts,Manouba, Tunisia
*Corresponding Author: Soura Boulaares, National School for Computer Science,Manouba, Tunisia.

Published: January 31, 2023

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Abstract  

Over the past few years, the use of electronic health records (EHRs), wearable devices and health apps has grown in popularity. Due to the abundance of collected and integrated data, self-management of health becomes more practical. Among the challenges facing the current health system are intelligent homes and intelligent workplaces made possible by the Internet of Things. The Web of Things (WoT) is a subset of the Internet of Things that aims to connect everyday things to the Internet and manage interoperability. Furthermore, collaboration of health data with data from various devices at home and at work, as well as open data on the Internet, is critical for successful and accessible health self-management. Unfortunately, shared health data may be untrustworthy for a variety of reasons. Uncertainty can be caused by heterogeneity, incompleteness, unavailability, and data inconsistency. To address the problem of health data uncertainty, we provide a probabilistic approach for composing uncertain Health Connected Data and computing the probabilities to deliver the final degree of uncertainty. We also present a method for parsing typical WoT objects into a new programmatic form that mimics the uncertainty of health data. Using a health care use case, we show how our technique successfully integrates uncertain health data with home, work, and sport environment data for the WoT domain.

Keywords: Uncertainty; WoT; uncertain IoT; REST Data; Integration; Probability