Open AccessUse of Artificial Intelligence for Face Detection with Face Mask in Real Time to Control the Entrance to an Entity
Author(s) -
Enrique Lee Huamaní,
Lilian Ocares Cunyarachi
Publication year - 2021
Publication title -
international journal emerging technology and advanced engineering
Language(s) - English
Resource type - Journals
ISSN - 2250-2459
DOI - 10.46338/ijetae1121_09
Subject(s) - control (management) , face (sociological concept) , computer science , identity (music) , security controls , field (mathematics) , identification (biology) , facial recognition system , artificial intelligence , adaptation (eye) , selection (genetic algorithm) , face detection , machine learning , computer security , risk analysis (engineering) , pattern recognition (psychology) , business , psychology , sociology , social science , physics , botany , mathematics , neuroscience , acoustics , pure mathematics , biology
Due to the pandemic caused by Covid-19, daily life has changed significantly. For this reason, biosecurity measures have been implemented to prevent the spread of the virus as an effective way to reactivate economic activities. In this sense, the present paper focuses on real-time face detection as a measure of control at the entrance to an entity, thus avoiding the spread of the virus while recognizing the identity of workers despite the use of masks and thus reducing the risk of entry of individuals outside the organization. Therefore, the objective is to contribute to the security of a company through the application of machine learning methodology. The selection of methodology is justified due to the adaptation of the same according to the interests of this project. Consequently, algorithms were used in a progressive manner, obtaining as a result the control system that was intended, since each particularity of the face of the individual was recognized in relation to its corresponding identification. Finally, the results of this article benefit the security of organizations regardless of their field or sector. Keywords— Control, Detection, Facial Recognition, Facial Mask, Face recognition, Machine learning.