In Real Time Face Mask Detection Alert System using CNN Model

Today's current scenario of the coronavirus pandemic (Covid19), where in the future there will be a need for efficient applications of real-time mask detection. Because, nowadays it is very difficult for doctors to handle patients infected with corona virus. Our major purpose of building a face-mask detection alert system using OpenCV that can detect individual person's if he/she is wearing a face mask or not wearing a face-mask using CCTV Camera, with quite a good accuracy. And also building and training the Convolutional Neural Network (CNN) using keras framework. After that, He / She refused to go to the locations or the regions wherever the officials were strictly asked to wear face-mask. After denying way in to the individual, the officers or the authorized person will receive an email in real time where the photograph of the person can be attached. In away screen panels could be installed at the entrances where the person's denied access can see a pop-up warning message. Where he/she would be advised to wear a face mask before getting access. This type of face mask detection alert system has some applications in schools, colleges, malls, theaters, offices and also other major crowded places or areas where it expects large public gathering. © 2022 IEEE.

Real Time Face Mask Detection by using CNN

The ongoing Covid-19 (coronavirus) outbreak is worsening the worldwide health crisis, impacting our daily lives. Wearing a face mask is the most basic form of prevention against coronavirus and also it is considered as one of the most significant survival suggestions. Nowadays, the correctness of wearing face masks is manually monitored, and it is impossible to alert people in overcrowded areas or public locations. For this reason, machine learning frameworks such as openCV, keras, scikit-learn, and tensorflow are employed. The proposed approach intends to develop a new way to automatically detect the correctness of face mask in human face. If no facemask is detected, the proposed model will inform or alert the concerned person. To detect face, an openCV with haar-cascade classifier is employed. The Convolutional Neural Network (CNN) model is also used to detect or train the proposed dataset, which includes the images of different persons with or without face mask. This technique leverages an accuracy of about 99.1%. © 2022 IEEE.