Smart Attendance System Utilizing Face Recognition Technology Based on Principal Component Analysis

Keeping track of attendance for daily activities is a difficult task. Because of the emergence of the coronavirus in late 2019, the world in general and the Sultanate of Oman in particular have become dangerous places that threaten the lives of ordinary people. Still, people should be careful while gathering or touching, and it is recommended that they wear masks everywhere, such as in schools, work, and hospitals. Students in their schools face the traditional attendance registration process daily, which requires touching if it is by handprint. As a result of the previous explanation, the problem can be identified; the virus can be transmitted among students by touching the handprint because of the traditional attendance registration process. This research uses artificial intelligence algorithms to create a smart attendance registration system. The system will eliminate the need for additional contact to record attendance and use artificial intelligence techniques to recognize the student’s face and record his name in the attendance file as soon as the student passes in front of the camera. The PCA algorithm was used in the practical part of this research to discover students’ faces and record their names. It showed the results of the PCA algorithm experiment using the confusion matrix method with high efficiency, where the accuracy rate reached 93% and the true positive was 100%. The results of the questionnaire showed the following percentages: 72.2% had heard of the smart attendance system, and 86.1% supported and agreed with the idea of applying the attendance system in schools.