Machine Learning-based System for Monitoring Social Distancing and Mask Wearing

Mohammed Faisal Naji,Chibli Joumaa, Yousef Alswailem, Abdulrahman Alobthni, Rayan Albusilan

2022 IEEE World AI IoT Congress (AIIoT)(2022)

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摘要
Coronavirus is a large family of viruses known to cause diseases ranging from the common cold to more serious diseases, and the methods for controlling epidemics of such viruses are difficult to deal with. One of the most dangerous things about COVID-19 is the speed with which it spreads. Therefore, we introduced a smart machine Iearning-based system for monitoring social distancing and mask wearing. The proposed system is used to monitor people and identify those who violate the rules of mask wearing or do not observe social distancing. It will help to control the epidemic, reduce the spread of COVID-19 and stress the importance of social distancing. The experimental results of the proposed system illustrate its robustness and accuracy.
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Covid-19,deep learning,Social Distancing,Mask Wearing
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