In the background of the COVID-19 pandemic, institutions such as the academy suffer a great deal from practically closed globally if the current situation is not going to change. COVID-19 also known as Serious Acute Respiratory Syndrome Corona virus-2 is an infectious disease that is released from an infected sick person who speaks, sneezes, or coughs by respiratory droplets. This spreads quickly through close contact with anyone infected, or by touching objects or surfaces affected with a virus. There's still currently no vaccine available to protect against COVID-19 and preventing exposure to the virus seems to be the only method to safeguard ourselves. Wearing a facemask that covers the nose and mouth in a public setting and often washing hands or the use of at least 70% alcohol-based sanitizers is one way to avoid being exposed to the virus. Amid the advancement of technology, Deep Learning has proven its effectiveness in recognition and classification through image processing. The research study uses deep learning techniques in distinguishing facial recognition and recognize if the person is wearing a facemask or not. The dataset collected contains 25,000 images using 224x224 pixel resolution and achieved an accuracy rate of 96% as to the performance of the trained model. The system develops a Raspberry Pi-based real-time facemask recognition that alarms and captures the facial image if the person detected is not wearing a facemask. This study is beneficial in combating the spread of the virus and avoiding contact with the virus.

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COVID-19 or Severe Acute Respiratory Syndrome Corona virus-2 is an extremely transmissible virus that is discharged through breathing droplets released from an infected individual who is talking, sneezing, or coughing. Close interaction with a person infected or through touching a contaminated surface and object can spread the virus rapidly. As of now, there is no vaccine to combat the COVID-19, and the best way to protect the person from a virus is to avoid being exposed to it. Wearing a facemask that covers the nose and mouth in a public setting and repeatedly cleansing of hands or the use of at least 70% alcohol-based disinfectants is a practice to avoid virus exposure. Deep Learning technology has demonstrated its achievement in recognition and classification by processing images. The research study uses deep learning techniques that identify if the person is wearing a facemask or not and check if the persons in the area observe physical distancing. The collected image data contains 20,000 images, uniformly crop images in 224x224 pixels, and attained an accuracy rate of 97% during the training of the model. The developed system is implemented using Python and OpenCV through TensorFlow that recognizes persons wearing a facemask or not wearing and measures the physical distance between each person. It signals an alarm and captures facial images upon detecting persons not wearing a mask and does not observe physical distancing. This study is beneficial in combating the spread of the virus and avoiding contact with the virus.

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