HUMAN ACTIVITY RECOGNITION (HAR) COMPUTER VISION SYSTEM USING DEEP LEARNING-BASED DETECTION CORONA (COVID-19) FOR PEOPLE MOBILIZATION
Abstract
The spread of disease will be difficult to detect in person who is active outside the home and requires a wide active wide of motion, person who feels healthy will leave the house ignoring normal body temperature conditions which are very dangerous, because some viruses will mutation and easily spread to other people especially if we are in same area public, the emergence of a virus in a person's body is the easiest to find the symptoms of body temperature above normal such as covid 19 disease and other diseases caused by fever and shortness of breath , the prevention solution is currently by placing several officers in other public places with measureon temperature using thermal sensors to detect body temperature above normal between 37C to 38C, if the temperature indication is found unhealth people need to prioritize and monitoring the health conducting further tests in the form of rapid tests and swabtest, the weakness of this monitoring is the number of person passing in public areas is very lot of people and disrupts the activities of especially those requiring high mobility need causes long and long-term checks. The inspection system able to carried out quickly, it is necessary for check and read with computer vision technology using thermal technology have capability and accurately for record body temperature, thermal data can read individual body conditions but unused directly in public areas, systems machine learning will provide a visual sign that can only be seen by the officer with the marking will make it easier for officers to indentify more person's condition and take action checking and prevention, this system has accuracy above 90% and usefull in masse and large public areas.
