Back to Search
Start Over
IoT and cloud-based COVID-19 risk of infection prediction using hesitant intuitionistic fuzzy set.
- Source :
-
Soft Computing - A Fusion of Foundations, Methodologies & Applications . Mar2024, Vol. 28 Issue 5, p3743-3755. 13p. - Publication Year :
- 2024
-
Abstract
- The outbreak of COVID-19 from Wuhan, China in 2019 has spread across the world, with more than 687 million confirmed coronavirus cases still increasing. Vaccines and medicines are one aspect of fighting the pandemic outbreak, but modern Information Technologies, web/ mobile-based technologies, blockchain, and Internet of Things (IoT) devices are being used to control the pandemic outbreak at an earlier/later stage. The IoT devices with sensors, and mobile apps/ websites having self-assessment tests can help in tracking COVID-19 infections. These people's tracking information and self-assessment tests are generating huge amounts of data. This white paper introduces an IoT and cloud-based architectural framework in the COVID-19 pandemic to predict infection risk based on citizens' self-assessments and storage of data in the cloud and the intelligent technique of hesitant Intuitionistic Fuzzy Set (IFS) has been used on the self-assessment dataset to predict the risk. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14327643
- Volume :
- 28
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- Soft Computing - A Fusion of Foundations, Methodologies & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 175389980
- Full Text :
- https://doi.org/10.1007/s00500-023-09548-0