ARTIFICIAL INTELLIGENCE BASED FACE MASKS DETECTION TECHNIQUES FOR PREVENTION OF COVID-19

Since the contagious coronavirus disease (COVID-19) had first been published in Wuhan, this has become a public health issue in China and even worldwide.This pandemic is wreaking havoc on economies and societies all over the world.The increased number of COVID-19 tests provides more information about the spread of the epidemic, which may improve the chances of neighbouring it to prevent further infections.Wearing a face mask that inhibits the transmission of droplets released into the air, as well as maintaining an appropriate external distance between people and reducing close contact, can still be beneficial in combating this pandemic.As a result, the objective of this paper is to provide a comprehensive analysis of artificially intelligent models that were used to discover face masks.It is deduced that the majority of the datasets used to detect face masks are artificially generated and do not represent real-world environments, which affects the highly precise model accuracy when deployed in the real world.On the contrary, real-world COVID-19 mask images are shared to model deep learning techniques.Additionally, in a real-time scenario, the usability and efficiency of these techniques are tracked down.It is further estimated that these technologies in conjunction with the existing embedded camera infrastructure can be used in a variety of verticals and can contribute to communal health.