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Adimora, K. C.
Department of Computer Engineering, Michael Okpara University of Agriculture Umudike, Umuahia Abia State, Nigeria
Aru, O. E.
Department of Computer Engineering, Michael Okpara University of Agriculture Umudike, Umuahia Abia State, Nigeria
ABSTRACT
The
traditional biometric system focuses mostly on security surveillance and has
little or no application in biomedicine. They are considered obsolete and not
resilient in solving the world’s present complex problems. In this paper, a
Biometric Artificial Intelligence (BAI) system capable of learning and adapting
to any situation was developed with Fuzzy Expert System (FES) and Support
Vector Machine (SVM) techniques that generates three premise inputs that
represent viral disease detection, treatment, and control. The BAI system was
designed to replace frontline health workers for viral disease (Covid-19)
testing and treatment so as to reduce the risk of person-to-person
transmission. The research result analysis showed that the BAI system is more
effective and efficient in carrying out viral disease testing and treatment
than humans. C# and MATLAB applications were used as the test bed for system
development and testing. Hopefully, the greater achievement will be made in the
health sector with the deployment of BAI technology.
Keywords: Biometric Artificial Intelligence, Biomedicine, Fuzzy Expert System, Support Vector Machine, Traditional Biometric.
https://doi.org/10.33922/j.ujet_v6i2_6
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Published
Friday, January 22, 2021
Issue
Vol. 6 No. 2, December 2020
Article Section
GENERAL
The contents of the articles are the sole opinion of the author(s) and not of UJET.
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