Biosensing epidemic and pandemic respiratory viruses: Internet of Things with Gaussian noise channel algorithmic model.

ABSTRACT

The current world condition is dire due to epidemics and pandemics as a result of novel viruses, such as influenza and the coronavirus, causing acute respiratory syndrome. To overcome these critical situations, the current research seeks to generate a common surveillance system with the assistance of a controlled Internet of Things operated under a Gaussian noise channel. To create the model system, a study with an analysis of H1N1 influenza virus determination on an interdigitated electrode (IDE) sensor was validated by current-volt measurements. The preliminary data were generated using hemagglutinin as the target against gold-conjugated aptamer/antibody as the probe, with the transmission pattern showing consistency with the Gaussian noise channel algorithm. A good fit with the algorithmic values was found, displaying a similar pattern to that output from the IDE, indicating reliability. This study can be a model for the surveillance of varied pathogens, including the emergence and reemergence of novel strains.