Contrivance of SSD-Mobilenets Algorithm-Based Smart Door Lock System for Discerning the Nano Face Mask to Restrain COVID-19 Transmission

Due to the COVID-19 outbreak, face masks have become essential for the human lifestyle, and with the advancement in disease control, nano face masks are widely used. Nano face masks can prevent the person wearing them from transmitting the virus causing COVID-19 to others. In this study, a facial recognition system was developed to control thieves in the digital society using nano face masks. Artificial Intelligence (AI) relies heavily on deep learning today because of its accuracy and automation in detecting the human face behind the nano face masks. A Single-Shot Detector (SSD), Region-based Convolution Neural Network (RCNN), Faster R-CNN, and You Only Look Once (YOLO) are the most famous object detection algorithms. With SSD and YOLO, efficient results are obtained compared to other algorithms; YOLO performs faster when preference is given to speed over accuracy. The deep learning technique combines SSD and MobileNets to improve detection and tracking performance. The developed algorithm is one of the most efficient object detection techniques behind the nano face masks compared to others. The application of the SSD algorithm with MobileNet for object identification and a microcontroller signal for the detection of nano face masks in public places such as universities, airports, hospitals, and workplaces resulted in ~99% accuracy; consequently, denying entry into public places for those who did not wear face masks.