Smart Attendance System Using Face Recognition for Tertiary Institutions in Nigeria

Student participation in a class is an important factor in a student's success in a course. It is one of the prerequisites for taking the exam at Nigerian universities and colleges. The traditional method of keeping track of student attendance in Nigerian institutions involves having each student sign their name on an attendance list that is sent around the class before lectures begin. This approach consumes time and increases the risk of fraud, especially in a crowded class. In some situations, the lecturer or teacher reads out the names of each student who signed on the attendance list to prevent proxy attendance. In this paper, a smart attendance system using face recognition is proposed to eliminate the problems of the manual method of attendance in Nigerian institutions. The proposed system maps the various courses to the available lecturers and teachers based on area of specialty, experience, and their current workload and keeps track of students' participation in the courses. The proposed smart attendance system was implemented and tested using a random set of students who enrolled in different courses. Based on the experimental results, the proposed system achieves face recognition accuracy of 100% and course-to-teacher mapping accuracy of 100%. With the level of performance shown by the system, it can be a useful tool for course-to-teacher mapping and student participation measurement.