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In particular, some researchers have focused on the hesitancy of governments in enacting difficult but necessary virus containment measures (e.g., stay-at-home orders and lockdowns), as well as noncooperation for reasons other than free riding. However, this COVID-19 management inefficacy can be additionally explored with game-theoretic scenarios beyond the public goods game. Therefore, to prevent rapid COVID-19 infection, many solutions, such as confinement and lockdowns, are suggested by the majority of the world’s governments. According to the centers for Disease Control and Prevention (CDC), coronavirus infection is transmitted predominantly by respiratory droplets produced when people breathe, talk, cough, or sneeze with common droplet size 5–10’m but aerosol emission increases when humans speak and shout loudly.
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The last statistics () provided by the World Health Organization (WHO) show 152,543452 confirmed cases and 3198528 deaths. īy now, the virus has rapidly spread to the majority of the countries worldwide. In addition, many sectors such as maintenance projects and infrastructure construction have not been suspended owing to their significant effect on people’s routine life.
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Many shutdowns in different industries have been caused by this pandemic. All over the world, especially in the third wave, COVID-19 has been a significant healthcare challenge. It is an emerging respiratory infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). This pandemic has devastating effects on societies and economies around the world causing a global health crisis.
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Since the end of 2019, infectious coronavirus disease (COVID-19) has been reported for the first time in Wuhan, and it has become a public damage fitness issue in China and even worldwide. This can be used with the existing embedded camera infrastructure to enable these analytics which can be applied to various verticals, as well as in an office building or at airport terminals/gates. Hence, this solution tracks the people with or without masks in a real-time scenario and ensures social distancing by generating an alarm if there is a violation in the scene or in public places. The system performs with F1-score of 99%, sensitivity of 99%, specificity of 99%, and an accuracy of 100%. The system performance is evaluated in terms of precision, recall, F1-score, support, sensitivity, specificity, and accuracy that demonstrate the practical applicability. This paper also provides a comparative study of different face detection and face mask classification models. After implementing and deploying the models, the selected one achieved a confidence score of 100%. People violating social distancing or not wearing masks were detected. The pretrained models such as the MobileNet, ResNet Classifier, and VGG are used in our context. Therefore, this research paper focuses on implementing a Face Mask and Social Distancing Detection model as an embedded vision system. However, wearing a face mask that prevents the transmission of droplets in the air and maintaining an appropriate physical distance between people, and reducing close contact with each other can still be beneficial in combating this pandemic. The increase in the number of COVID-19 tests gives more information about the epidemic spread, which may lead to the possibility of surrounding it to prevent further infections. This pandemic is having devastating effects on societies and economies around the world. Since the infectious coronavirus disease (COVID-19) was first reported in Wuhan, it has become a public health problem in China and even around the world.