dc.contributor.author |
Fagbola, Temitayo Matthew
|
|
dc.contributor.author |
Fagbola, Funmilola Ikeolu
|
|
dc.contributor.author |
Aroba, Oluwasegun Julius
|
|
dc.contributor.author |
Doshi, Ruchi
|
|
dc.contributor.author |
Hiran, Kamal Kant
|
|
dc.contributor.author |
Thakur, Surendra Colin
|
|
dc.date.accessioned |
2023-12-04T09:21:38Z |
|
dc.date.available |
2023-12-04T09:21:38Z |
|
dc.date.issued |
2023-01 |
|
dc.description.abstract |
Smart sensing technology has been playing tremendous roles in digital healthcare management over time with great impacts. Lately, smart sensing has awoken the world by the advent of smart face masks (SFMs) in the global fight against the deadly Coronavirus (Covid-19) pandemic. In turn, a number of research studies on innovative SFM architectures and designs are emerging. However, there is currently no study that has systematically been conducted to identify and comparatively analyze the emerging architectures and designs of SFMs, their contributions, socio-technological implications, and current challenges. In this article, we investigate the emerging SFMs in response to Covid-19 pandemic and provide a concise review of their key features and characteristics, design, smart technologies, and architectures. We also highlight and discuss the socio-technological opportunities posed by the use of SFMs and finally present directions for future research. Our findings reveal four key features that can be used to evaluate SFMs to include reusability, self-power generation ability, energy awareness and aerosol filtration efficiency. We discover that SFM has potential for effective use in human tracking, contact tracing, disease detection and diagnosis or in monitoring asymptotic populations in future pandemics. Some SFMs have also been carefully designed to provide comfort and safety when used by patients with other respiratory diseases or comorbidities. However, some identified challenges include standards and quality control, ethical, security and privacy concerns. |
en_US |
dc.description.department |
Computer Science |
en_US |
dc.description.librarian |
hj2023 |
en_US |
dc.description.sdg |
None |
en_US |
dc.description.uri |
https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7361 |
en_US |
dc.identifier.citation |
Fagbola, T.M., Fagbola, F.I., Aroba, O.J. et al. 2023, 'Smart face masks for Covid-19 pandemic management: a concise review of emerging architectures, challenges and future research directions', IEEE Sensors Journal, vol. 23, no. 2, pp. 877-888, doi : 10.1109/JSEN.2022.3225067. |
en_US |
dc.identifier.issn |
1530-437X (print) |
|
dc.identifier.issn |
1558-1748 (online) |
|
dc.identifier.other |
10.1109/JSEN.2022.3225067 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/93596 |
|
dc.language.iso |
en |
en_US |
dc.publisher |
Institute of Electrical and Electronics Engineers |
en_US |
dc.rights |
© 2023 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. |
en_US |
dc.subject |
Aerosol |
en_US |
dc.subject |
Smart sensing |
en_US |
dc.subject |
Smart face mask (SFM) |
en_US |
dc.subject |
Pandemic management |
en_US |
dc.subject |
Nanotechnology |
en_US |
dc.subject |
Material science |
en_US |
dc.subject |
Mask technology |
en_US |
dc.subject |
COVID-19 pandemic |
en_US |
dc.subject |
Coronavirus disease 2019 (COVID-19) |
en_US |
dc.subject |
Wearable computers |
en_US |
dc.subject |
Sensors |
en_US |
dc.subject |
Pandemic |
en_US |
dc.subject |
Frequency modulation |
en_US |
dc.subject |
Diseases |
en_US |
dc.subject |
Medical information systems |
en_US |
dc.subject |
Intelligent sensors |
en_US |
dc.subject |
Health care |
en_US |
dc.subject |
Data privacy |
en_US |
dc.subject |
Epidemics |
en_US |
dc.title |
Smart face masks for Covid-19 pandemic management : a concise review of emerging architectures, challenges and future research directions |
en_US |
dc.type |
Postprint Article |
en_US |