Computational Biomedical Framework Using IoT and MR for Detecting, Tracking and Preventing Asymptomatic COVID-19 Patients

Abstract

This article proposes a novel biomedical system integrating Internet of Things (IoT) and Mixed Reality (MR) technologies for detecting, tracking and preventing asymptomatic COVID patients from entering into public places which prevents the further spread of COVID-19 infection. Asymptomatic patients are the very active carriers for virus transmission and the most challenging condition in mitigating the virus transmission are contact tracking and contact tracing of asymptomatic patients. The proposed system can be implemented in public places such as theatres, malls, railway stations, airport, markets, conferences, and other gatherings for screening people to detect asymptomatic COVID patients and restrict them from entry. The arrest or decrease in spread of COVID infection during pandemic situation is the most challenging factor around the globe. However, with the proposed system, detection and prevention of asymptomatic COVID patients will result in drastic decrease in the spread of COVID infection during pandemic situation. The proposed system comprises of an IoT based sensing system to get the current sensor values and an MR vision software system to retrieve the pre-saved sensor values from the server. The MR vision system compares the present sensor values and the server values of the human and displays accurately with green MR images for permitted persons and red MR images for restricted asymptomatic COVID patients.