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Biosensing epidemic and pandemic respiratory viruses: Internet of Things with Gaussian noise channel algorithmic model
Author(s) -
Gopinath Subash C.B.,
Ismail Zool H.,
Sekiguchi Kazuma
Publication year - 2022
Publication title -
biotechnology and applied biochemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.468
H-Index - 70
eISSN - 1470-8744
pISSN - 0885-4513
DOI - 10.1002/bab.2300
Subject(s) - pandemic , virology , noise (video) , covid-19 , internet of things , channel (broadcasting) , computer science , biosensor , computational biology , biology , artificial intelligence , medicine , computer security , telecommunications , disease , pathology , infectious disease (medical specialty) , image (mathematics) , biochemistry , outbreak
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.