Biosensing epidemic and pandemic respiratory viruses: Internet of things with gaussian noise channel algorithmic model.
Subash C B GopinathZool Hilmi IsmailKazuma SekiguchiPublished in: Biotechnology and applied biochemistry (2021)
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 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 interdigitated electrode, indicating reliability. This study can be a model for the surveillance of varied pathogens, including the emergence and re-emergence of novel strains. This article is protected by copyright. All rights reserved.
Keyphrases
- sars cov
- air pollution
- public health
- liver failure
- health information
- machine learning
- healthcare
- gold nanoparticles
- deep learning
- coronavirus disease
- photodynamic therapy
- respiratory failure
- social media
- case report
- high resolution
- mass spectrometry
- artificial intelligence
- sensitive detection
- molecularly imprinted
- silver nanoparticles
- simultaneous determination