A Deep-Learning-Based Edge-Centric COVID-19-Like Pandemic Screening and Diagnosis System within a B5G Framework Using Blockchain
Ghulam Muhammad, M. Shamim Hossain
Abstract
Beyond 5G (B5G) has the potential of realizing all three pillars of 5G, which are massive type communication, ultra-reliable low latency communication, and enhanced mobile broadband. Currently, a COVID-19-like pandemic can utilize B5G to combat the pandemic by using real-time processing of massive volumes of test data at the edge of hospitals and by leveraging seamless communication between the edge and a global core cloud to update any diagnosis or predicting model globally. In this article, we propose an artificial-intelligence-enabled edge-centric COVID-19 screening and diagnosis system using the B5G network. Furthermore, we use blockchain-based secure transmission of patients' data in the edge. The proposed system uses screening and diagnosis in the edge by using powerful edge devices that can run deep learning (DL) models. The DL models can be downloaded from the core cloud to the edge server or uploaded to the core cloud when necessary.