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AuthorKhan, Hameed
AuthorKushwah, K. K.
AuthorSingh, Saurabh
AuthorUrkude, Harshika
AuthorMaurya, Muni Raj
AuthorSadasivuni, Kishor Kumar
Available date2023-10-08T08:41:45Z
Publication Date2021
Publication Name3 Biotech
ResourceScopus
ISSN2190572X
URIhttp://dx.doi.org/10.1007/s13205-020-02581-y
URIhttp://hdl.handle.net/10576/48309
AbstractThe novel coronavirus infection (COVID-19) is not diminishing without vaccine, but it impinges on human safety and economy can be minimized by adopting smart technology to combat pandemic situation. The implementation of new innovations and novel tactics has proven to be effective in curbing the risk of COVID-19. The present study covers the role of smart technology in mitigating the spread of COVID-19 with specific focus on advancement in the field of drone, robotics, artificial intelligence (AI), mask, and sensor technology. The findings shed light on the robotics and drone technology-driven approaches that have been applied for assisting health system, surveillance, and disinfection process, etc. The AI technology strategies and framework is highlighted in terms of bulk data computing, predicting infection threats, providing medical assistance, and analyzing diagnosis results. Besides this, the technological shift in mask and sensor technology during the pandemic have been illustrated, which includes fabrication method like 3D printing and optical sensing, respectively. Furthermore, the strength, weakness, opportunities, and possible threats that have been shaped by the rigorous implementation of these technologies are also covered in detail.
SponsorThis work was carried by the RRC grant # RRC-2-063 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.
Languageen
PublisherSpringer Science and Business Media Deutschland GmbH
SubjectArtificial intelligence
COVID-19
Drone
Mobile apps
Robot
Sensor
TitleSmart technologies driven approaches to tackle COVID-19 pandemic: a review
TypeArticle Review
Issue Number2
Volume Number11
dc.accessType Abstract Only


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