IoT based automated entry system with integration of Covid-19 symptom detection

Abstract

COVID-19 has stopped the normal life since December 2019. We still cannot go out without worrying about getting infected by this deadly virus. Although offices and other work places have started to open, they have to maintain a health protocol set by WHO (World Health Organization). The main reason for this outbreak is the irresponsibility of the people and the authorities regarding maintaining the health protocols. As people do not maintain the health protocols properly, the safety in a work environment is breached and the virus starts to spread. After extended period of lockdown, the world is again returning to its old state by gradually opening the educational institutions and offices. So, to maintain the health protocol with notable integrity, the development of an Internet of Things (IoT)-based Automated Entry System with COVID-19 Symptom Detection is an attempt to reduce COVID-19's spread through making aware people of their conditions. This is accomplished by first developing an RFID-based entry and log data base, then employing a machine learning model to recognize face masks so that the device can detect unauthorized intruder and distinguish between mask and non-mask users. After that the non contact temperature sensor and an oximeter sensor will take physical data to cross check with COVID-19 symptoms. This way the device can determine the risk factor of being a COVID-19 virus carrier.