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Journal of Information and Organizational Sciences, Vol. 49 No. 1, 2025.

Izvorni znanstveni članak

https://doi.org/10.31341/jios.49.1.8

Smart Real-time Attendance System for Nigerian Universities

Mikailu Habila orcid id orcid.org/0009-0009-3274-4585 ; Department of Computer Science, Nigerian Army University, Biu, Nigeria
Faseki N. Francisca ; Department of Computer Science, Nigerian Army University, Biu, Nigeria
Luwani Ishaya ; Department of Computer Science, Nigerian Army University, Biu, Nigeria
Muhammed Kabir Ahmed ; Department of Computer Science, Gombe State University, Gombe, Nigeria
Umar A. Muhammad ; Department of Computer Science, Nigerian Army University, Biu, Nigeria
Haruna P. Charles ; Department of Computer Science, Nigerian Army University, Biu, Nigeria

Puni tekst: engleski pdf 4.677 Kb

str. 121-138

preuzimanja: 178

citiraj

Sažetak

This study proposes a Smart Real-Time Attendance System using face recognition technology to address challenges in traditional attendance systems in Nigerian universities. These challenges include proxy attendance, manual errors, and administrative inefficiencies. The system employs Convolutional Neural Networks (CNNs) and the ArcFace algorithm for facial feature extraction and identity verification. Key development tools included InsightFace, OpenCV, and Streamlit, with Visual Studio Code as the IDE. The system ensures high accuracy, with 94% face detection, 98% face recognition, and 96% overall attendance prediction accuracy. It automates essential tasks like attendance percentage calculation and report generation, ensuring compliance with the National Universities Commission (NUC) 75% attendance requirement for exam eligibility. Ethical compliance was a core design concern, including informed consent, data encryption, access control, and fairness across facial profiles. This system significantly reduces impersonation, administrative workload, and enhances operational efficiency, making it a scalable and secure solution for attendance management. Its deployment is recommended for improving academic monitoring and policy enforcement in Nigerian universities.

Ključne riječi

Smart Attendance System; Face Recognition Technology; Convolutional Neural Networks; Real-Time Attendance Monitoring; Automated Student Verification

Hrčak ID:

332019

URI

https://hrcak.srce.hr/332019

Datum izdavanja:

30.6.2025.

Posjeta: 671 *