AUTOMATED SCREENING SYSTEM OF COVID-19 INFECTED PERSONS BY MEASUREMENT OF RESPIRATORY DATA THROUGH DEEP FACIAL RECOGNITION

AUTOMATED SCREENING SYSTEM OF COVID-19 INFECTED PERSONS BY MEASUREMENT OF RESPIRATORY DATA THROUGH DEEP FACIAL RECOGNITION Abstract: More than 10 00 000 people were exposed to the novel coronavirus called COVID 19, which is transpired in Wuhan, China, in December 2019 and became a worldwide medical evacuation rapidly. Vigorous medication and enhanced allotment of hospital facilities in pandemic regions are substantial due to the increased rate of infectious disease. Precise and efficient medication helps to segregate the suspected cases to stabilize the spreading of infection. A severe hurdle is the lack of hospital and medical facilities in pandemic regions. COVID-19isan irregular breathing condition triggered by coronavirus infections, so numerous citizens typically wear masks to reduce the threats of being infected during the pandemic period. This invention presents FLIR E6 that uses RGB and thermal cameras for health screening to acquire the facial expressions in video frames. YOLO V3 is suggested for detecting the facial regions such as the forehead part and nostril areas. Based on the detection of the accurate region, the respiration data is extracted from the masked nostril region. Inevitably, the recurrent neural network model called Long Short Term Memory proposes for classifying as infected or healthy people based on respiratory data. This proposal exhibits that the contactless and smart screening test, which exploits the pre-scan process for virally infected people with high accuracy of detection and obtains relatively high performance. 11 P a g e AUTOMATED SCREENING SYSTEM OF COVID-19 INFECTED PERSONS BY MEASUREMENT OF RESPIRATORY DATA THROUGH DEEP FACIAL RECOGNITION Diagram breathing data iae andmaskdetection detection usn YOLO V3 FLIR thermal camera Iht xtt viralInfectedperson SflR classification using LSTM normalperson Fig 1: Data flow diagram 1| P a g e