Smart Facial Mask Detector

Abstract

The COVID-19 pandemic has resulted in a significant loss of human life throughout the globe, and it poses an unprecedented threat to public health, food systems, and the workplace. This coronavirus, according to the World Health Organization, emerged in late December 2019 in Wuhan, China. The virus has been identified as infectious and transmissible by air or close contact with an infected person after extensive investigation. Many precautions have been recommended to prevent the transmission of this virus, including maintaining a social distance, or keeping a suitable physical space between individuals and avoiding close contact, and wearing a face mask to prevent the virus from spreading via the wind. As a result, the goal of this research work is to develop and implement a Face Mask Detection System. Object detection and face identification will be included into the video footage of college campuses by these systems. OpenCV, Image preprocessing, and KNN algorithms are among the models employed. An individual whose face was discovered without the use of face masks. The number of persons violating or non-violating the relevant activities is shown on the complete results board in the output. This research endeavor received a 100 percent confidence score after applying and building the models. As a result, this study effort culminates with the established fact that wearing face masks reduces viral spread and so creates a model to assist identify these behaviors.