A Versatile Data Fabric for Advanced IoT-Based Remote Health Monitoring
Italo Buleje, Vince S. Siu, Kuan Yu Hsieh, Nigel Hinds, Bing Dang,, Erhan Bilal, Thanhnha Nguyen, Ellen E. Lee, Colin A. Depp, Jeffrey L. Rogers

TL;DR
This paper introduces a flexible, secure data fabric architecture and toolkit for integrating diverse IoT health data sources, enabling unified dashboards and reusable components for digital health research and remote monitoring.
Contribution
It presents a novel data fabric architecture with open-source components that facilitate heterogeneous data integration and deployment in cloud or on-premises environments for digital health.
Findings
Successful implementation in a home telemonitoring project for older adults
Enhanced data integration from multiple IoT devices and applications
Streamlined data management for health monitoring research
Abstract
This paper presents a data-centric and security-focused data fabric designed for digital health applications. With the increasing interest in digital health research, there has been a surge in the volume of Internet of Things (IoT) data derived from smartphones, wearables, and ambient sensors. Managing this vast amount of data, encompassing diverse data types and varying time scales, is crucial. Moreover, compliance with regulatory and contractual obligations is essential. The proposed data fabric comprises an architecture and a toolkit that facilitate the integration of heterogeneous data sources, across different environments, to provide a unified view of the data in dashboards. Furthermore, the data fabric supports the development of reusable and configurable data integration components, which can be shared as open-source or inner-source software. These components are used to…
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