An Access Control System for Covid19 Using Computer Vision and Deep Learning Techniques: A Aystematic Review

https://doi.org/10.48185/jaai.v3i1.458

Authors

Abstract

After the emergence of the Coronavirus disease (Covid19) in December, 2019 the virus was confirmed by the World Health Organization (WHO) to be a dangerous virus that spread through airborne and droplets. One of the most effective way of preventing the spread of this virus is the use of facemask in public places such as banks, shopping mall, schools, offices and the likes. For this reasons people are advised to use facemask whenever they go out for their daily activities. However, some people have refused to wear the facemask in public places, thereby increasing the rate at which the virus spreads. Hence, there is a need to design an access control system for use in public places to grant access to people complying with the facemask regulations or deny access to those faulting them. Literature has shown that the use of computer vision and deep learning technology can play important role in the deployment of such access control system for face detection and facemask detection. The computer vision and deep learning techniques used in face recognition and facemask detection are describes in this systematic literature review.

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Author Biographies

Emeka Ogbuju, Federal University Lokoja

Department of Computer Science. Lecturer.

Francisca Oladipo, Federal University Lokoja

Department of Computer Science. Head of Department.

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Published

2022-06-30

How to Cite

Abiodun, T., Ogbuju, E., & Oladipo, F. (2022). An Access Control System for Covid19 Using Computer Vision and Deep Learning Techniques: A Aystematic Review. Journal of Applied Artificial Intelligence, 3(1), 34–46. https://doi.org/10.48185/jaai.v3i1.458

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Articles