Published Paper Details:

Coronavirus has impacted practically every element of people's lives since December 2019. Even today, this remains a cause of distress for millions of people and businesses. According to studies, wearing a face mask and checking your temperature on a regular basis minimizes the risk of viral transmission and gives a sense of security. To avoid the spread of viral illness, the use of face masks and temperature checks in public locations must be rigorously monitored. It is not possible to manually monitor the processes of many persons. It is necessary to develop a smart system that can determine whether an individual is wearing a mask on his or her face and has a normal body temperature. The model shows how the face mask and temperature detection analysis are automated without the need for human intervention. Image processing and deep learning are used to recognize people's faces and classify them into two groups: those who wear masks and those who do not. The model has been trained using the MobileNetV2 architecture and is implemented using several python libraries such as Tenforflow, Keras, and opencv. The model has an infrared sensor for measuring the temperature of the human body. With this model, an individual who is responsible for monitoring people can sit in a remote location and still monitor effectively and take appropriate action. This device can be utilized as a digital scanning instrument at the entry of schools, hospitals, banks, and airports, among other places.