Paper accepted: Container-based Data Pipelines on the Computing Continuum for Remote Patient Monitoring

Container-based Data Pipelines on the Computing Continuum for Remote Patient Monitoring

Authors: Nikolay Nikolov, Arnor Solberg, Radu Prodan, Ahmet Soylu, Mihhail Matskin, Dumitru Roman

Computer Jounal, Special Issue on Computing in Telemedicine

Abstract: Diagnosing, treatment, and follow-up care of patients is happening increasingly through telemedicine, especially in remote areas where direct interaction is hindered. Over the past three years, following the COVID-19 pandemic, the utility of remote patient care has been further field-tested. Tackling the technical challenges of a growing demand for telemedicine requires a convergence of several fields: 1) software solutions for reliable, secure, and reusable data processing, 2) management of hardware resources (at scale) on the Cloud/Fog/Edge Computing Continuum, and 3) automation of DevOps processes for deployment of digital healthcare solutions with patients. In this context, the emerging concept of \emph{big data pipelines} provides relevant solutions and is one of the main enablers. In what follows, we present a data pipeline for remote patient monitoring and show a real-world example of how data pipelines help address the stringent requirements of telemedicine.