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Title |
Smart Attendance Management System |
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Author |
Alaa Albahrani, Zainab Ali AL-Ali, Zainab Yousef Al-Ali, Aqeela Al-Mssri, Mashael AL-Shalan, Atta-ur-Rahman, and Gomathi Krishnasamy |
| Citation |
Vol. 22 No. 6 pp. 762-770 |
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Abstract |
Keeping track of attendance while engaging students in the classroom may be tough, especially when the class is big. The conventional method of calling pupils' names is tedious and time-consuming, and proxy attendance is always a possibility. To address this problem and maintain track of students' attendance, we presented a smart attendance management system (SAMS) using face recognition, fingerprints, and location. SAMS assists the instructor in two ways. First, it provides an automatic and error-free rollcall. Second, it records the attendance of pupils over time to share with the advising unit, and to generate a DN list of students with short attendance before the exam for the academic affairs unit. SAMS notifies students when the rollcall window on their smartphone is activated/opened, based on the precise date/time slot for a class (under instructor ID, subject ID, and classroom location). It allows students to register for classes using their smartphone's face recognition and/or fingerprint sensor. As a result, the student's rollcall is recorded in the system, along with the classroom location identifier. The system uses deep learning (DL) approaches for biometrics, such as the histogram of oriented gradient approach for facial and fingerprint recognition. The proposed system can also be used for rollcall in online classrooms. |
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Keywords |
SAMS, smart rollcall, Location based services, DN list, face recognition, fingerprints. |
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