Digital Twins-Based Data Fabric Architecture to Enhance Data Management in Intelligent Healthcare Ecosystems

Abstract

Different kind of smart healthcare ecosystems have been adopted in the last few years usually based on the continuous monitoring of people as well as other physical entities such as buildings or devices. The diverse nature and origins of the great amount of data that those novel smart healthcare ecosystems must process poses additional data management issues that restrict and difficult their design and construction. In order to improve data management in smart healthcare ecosystems, a data fabric architecture-like process for data lifecycle management has been obtained from the analysis of different architectural proposals intended for being used for different types of systems and contexts. This process integrates aspects of Digital Twins (DT) to tackle with the data contextualization problems that characterizes data fabric architectures. Based on the proposed approach, a prototype of a novel smart healthcare Internet of Things (IoT)-based ecosystem to prevent the spreading of the virus in a real Spanish nursing home has been developed. The evaluation of the prototype has been carried out following a specific novel IoT-based systems evaluation methodology combined with ISO software quality standards that determined that the system is reliable and efficient in performance.