Face mask detection and recognition using an IoT enabled PDMS-Ag e-skin sensor that works in contact and non-contact modes

The COVID-19 pandemic has already spread over 200 countries in a few months and taken a toll on many lives. At this critical time, there is a need to follow some precautions to control the virus spreading rapidly through direct and indirect contact. The World Health Organization (WHO) has already recommended the importance of face masks for protection from the virus. Hence, one of the prime changes we have had to incorporate in our lives is wearing a face mask. This work reports the development of Ag particles containing polydimethylsiloxane (PDMS) based e-skin sensor, which generates signals on touch (contact mode) or proximity (non-contact mode) near the sensor. These signals are retrieved using IoT. The signals indicate a person's presence, which activates face mask detection using deep learning. This model is an IoT and Machine Learning-based system. When a human touches or places a hand near the PDMS-Ag sensor, this model performs face masks detection. This model is also suitable for security purposes. Since controlling the number of new COVID-19 cases is the need of the hour, we are using face mask detection in this study.