Biometric Attendance System Using Face Recognition initiative offers a game-changing answer to the age-old problem of tracking attendance. This innovative solution uses face recognition technology to automate attendance management, providing accuracy, efficiency, and security. The project, which was created on the Android platform, makes use of the capabilities of Kotlin as the core programming language. TensorFlow, a strong machine learning framework, enhances the system's functionality by assisting in real-time face detection and recognition. Android Studio, a versatile IDE designed for Android app development, was the development environment of choice. A careful data collection strategy that included observation and interviews yielded useful insights into the limits of traditional manual attendance systems. The algorithm performs facial feature extraction, comparison, and matching against the stored biometric data to determine the identity of the individual. To ensure data privacy and security, the system employed advanced encryption techniques to protect the biometric data stored in the database. Additionally, measures are in place to prevent unauthorized access to the system and its sensitive information. The Biometric Attendance System offers several advantages over traditional attendance methods. It eliminates the need for manual recording and reduces the potential for errors or fraudulent practices, resulting in more accurate attendance records. The system provides real-time attendance updates to teachers and administrators, enabling timely intervention for absentees. The automation of attendance processes also saves valuable time.
| Published in | International Journal of Sustainable Development Research (Volume 9, Issue 4) |
| DOI | 10.11648/j.ijsdr.20230904.12 |
| Page(s) | 68-78 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2023. Published by Science Publishing Group |
Biometric, Accuracy, Privacy, Security, Recognition, Face Acceptance Rate, Initiative
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APA Style
Ukamaka Betrand, C., Juliet Onyema, C., Eberechi Benson-Emenike, M., Allswell Kelechi, D. (2023). Authentication System Using Biometric Data for Face Recognition. International Journal of Sustainable Development Research, 9(4), 68-78. https://doi.org/10.11648/j.ijsdr.20230904.12
ACS Style
Ukamaka Betrand, C.; Juliet Onyema, C.; Eberechi Benson-Emenike, M.; Allswell Kelechi, D. Authentication System Using Biometric Data for Face Recognition. Int. J. Sustain. Dev. Res. 2023, 9(4), 68-78. doi: 10.11648/j.ijsdr.20230904.12
AMA Style
Ukamaka Betrand C, Juliet Onyema C, Eberechi Benson-Emenike M, Allswell Kelechi D. Authentication System Using Biometric Data for Face Recognition. Int J Sustain Dev Res. 2023;9(4):68-78. doi: 10.11648/j.ijsdr.20230904.12
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Download@article{10.11648/j.ijsdr.20230904.12,
author = {Chidi Ukamaka Betrand and Chinazo Juliet Onyema and Mercy Eberechi Benson-Emenike and Douglas Allswell Kelechi},
title = {Authentication System Using Biometric Data for Face Recognition},
journal = {International Journal of Sustainable Development Research},
volume = {9},
number = {4},
pages = {68-78},
doi = {10.11648/j.ijsdr.20230904.12},
url = {https://doi.org/10.11648/j.ijsdr.20230904.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsdr.20230904.12},
abstract = {Biometric Attendance System Using Face Recognition initiative offers a game-changing answer to the age-old problem of tracking attendance. This innovative solution uses face recognition technology to automate attendance management, providing accuracy, efficiency, and security. The project, which was created on the Android platform, makes use of the capabilities of Kotlin as the core programming language. TensorFlow, a strong machine learning framework, enhances the system's functionality by assisting in real-time face detection and recognition. Android Studio, a versatile IDE designed for Android app development, was the development environment of choice. A careful data collection strategy that included observation and interviews yielded useful insights into the limits of traditional manual attendance systems. The algorithm performs facial feature extraction, comparison, and matching against the stored biometric data to determine the identity of the individual. To ensure data privacy and security, the system employed advanced encryption techniques to protect the biometric data stored in the database. Additionally, measures are in place to prevent unauthorized access to the system and its sensitive information. The Biometric Attendance System offers several advantages over traditional attendance methods. It eliminates the need for manual recording and reduces the potential for errors or fraudulent practices, resulting in more accurate attendance records. The system provides real-time attendance updates to teachers and administrators, enabling timely intervention for absentees. The automation of attendance processes also saves valuable time.
},
year = {2023}
}
TY - JOUR T1 - Authentication System Using Biometric Data for Face Recognition AU - Chidi Ukamaka Betrand AU - Chinazo Juliet Onyema AU - Mercy Eberechi Benson-Emenike AU - Douglas Allswell Kelechi Y1 - 2023/11/17 PY - 2023 N1 - https://doi.org/10.11648/j.ijsdr.20230904.12 DO - 10.11648/j.ijsdr.20230904.12 T2 - International Journal of Sustainable Development Research JF - International Journal of Sustainable Development Research JO - International Journal of Sustainable Development Research SP - 68 EP - 78 PB - Science Publishing Group SN - 2575-1832 UR - https://doi.org/10.11648/j.ijsdr.20230904.12 AB - Biometric Attendance System Using Face Recognition initiative offers a game-changing answer to the age-old problem of tracking attendance. This innovative solution uses face recognition technology to automate attendance management, providing accuracy, efficiency, and security. The project, which was created on the Android platform, makes use of the capabilities of Kotlin as the core programming language. TensorFlow, a strong machine learning framework, enhances the system's functionality by assisting in real-time face detection and recognition. Android Studio, a versatile IDE designed for Android app development, was the development environment of choice. A careful data collection strategy that included observation and interviews yielded useful insights into the limits of traditional manual attendance systems. The algorithm performs facial feature extraction, comparison, and matching against the stored biometric data to determine the identity of the individual. To ensure data privacy and security, the system employed advanced encryption techniques to protect the biometric data stored in the database. Additionally, measures are in place to prevent unauthorized access to the system and its sensitive information. The Biometric Attendance System offers several advantages over traditional attendance methods. It eliminates the need for manual recording and reduces the potential for errors or fraudulent practices, resulting in more accurate attendance records. The system provides real-time attendance updates to teachers and administrators, enabling timely intervention for absentees. The automation of attendance processes also saves valuable time. VL - 9 IS - 4 ER -
Department of Computer Science, School of Information and Communication Technology, Federal University of Technology, Owerri, Nigeria
