DEVELOPMENT OF A BIOMETRIC, FACIAL RECOGNITION AND AUTHENTICATION SYSTEM FOR CLASS ATTENDANCE MANAGEMENT
- Authors
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Ojo Oluwole Timothy
Federal University of Technology, Akure, Ondo State, P.M.B.704, Nigeria
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2Adeniji Toyosi Adelowokan
Prototype Engineering Development Institute, P.M.B. 5025 Ilesha, Osun State, Nigeria;
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- Keywords:
- Attendance Management, Automation, Biometric, Facial Recognitions Introduction
- Abstract
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The paper presents the development of a Class Attendance Management System (CAMS) that addresses the limitations of traditional manual attendance methods, such as errors in recording, time consumption, and data handling inefficiencies. The CAMS is made up of fingerprint enrollment and authentication, and facial recognition, implemented through Python’s face recognition module, ensuring accuracy and reducing impersonation. The system integrates biometric fingerprint scanning and facial recognition using hardware components such as; a fingerprint scanner, facial detection modules, and an Arduino ESP32 microcontroller. Software tools such as Python 3.11, SQL, and Google Sheets are employed for data processing and storage. CAMS features a user-friendly interface, real-time attendance recording, and secure data management. The attendance records are stored in Excel form for future reference. Performance metrics of the developed system show high accuracy, with a 0.01% false acceptance rate (FAR), a 0.02% false rejection rate (FRR), and an average recognition response time of 1.2 seconds. The developed CAMS provides accurate data, enhances administrative efficiency, supports lecture planning and delivery, thus minimizing the drawbacks of traditional methods of attendance management.
- Author Biographies
- References
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- Published
- 2025-05-30
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