The Novel E-Way of Identifying the Face Mask and To Ware the System in the Crowd Management System

Since World War II, the Coronavirus has been the most critical charity test the world has faced. The globe has fought the epidemic with incredible bravery, and the early phases have been particularly heart-breaking. Correctly wearing a veil had shown to be an effective method of limiting the transmission of illness. We're working on developing a technique that will allow us to detect fine-grained veil wear issues. There are three primary obstacles to overcome in this project: 1) a variety of facial expressions, 2) a variety of veil types and instances; and 3) a variety of facial impediments We built a new, reasonable dataset of 4000 photos to figure out what was causing the issues. The proposed method is to leverage SSD with Caffe and MobileNetV2 engineering as a picture classifier to provide continuous veil recognition. The accuracy of this model is 96 percent. On this decent dataset, more high-level models for warm scanning and facial recognition are constructed.