SECURING ORGANIZATIONAL OPERATIONS: AN ELECTRONIC GATE SYSTEM INTEGRATING FACIAL RECOGNITION FOR ATTENDANCE TRACKING AND ACCESS CONTROL

Efficient staff attendance management is a pivotal aspect of organizational success. The detrimental impact of poor staff attendance underscores the need for effective attendance monitoring methods. Automated approaches have emerged as solutions to mitigate the challenges associated with manual attendance tracking. From traditional paper-based methods to advanced technologies like radio frequency identification (RFID) and biometrics, the evolution of attendance monitoring techniques has significantly enhanced operational efficiency. Biometric-based attendance systems, leveraging unique physiological and behavioral attributes, have gained prominence due to their accuracy and security features. This study presents the development of an innovative electronic gate system employing facial recognition technology to regulate access and monitor staff attendance within organizational contexts. Facial recognition technology offers a balance between accuracy and privacy concerns, rendering it an ideal choice for identity verification applications. The proposed system utilizes strategically positioned cameras at access points to recognize staff members based on their facial features. A comprehensive database stores individual staff profiles, complete with associated images, facilitating seamless identification and attendance record-keeping. An integral facet of this system is the integration of an automatic penalization mechanism to deter tardiness. This mechanism deducts a predetermined amount from an employee's salary for each instance of punctuality violation. To address security vulnerabilities like tailgating, a weight verification feature has been incorporated to ensure that only authorized personnel gain access.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-13
DOI
https://doi.org/10.5281/zenodo.14133768
Citations
1
Primary Topic
Emotion and Mood Recognition
Type
article
Field-Weighted Citation Impact
0.51
Controls
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article

SECURING ORGANIZATIONAL OPERATIONS: AN ELECTRONIC GATE SYSTEM INTEGRATING FACIAL RECOGNITION FOR ATTENDANCE TRACKING AND ACCESS CONTROL

1 citations
Zenodo (CERN European Organization for Nuclear Research)
Emotion and Mood Recognition
0.51
article

SECURING ORGANIZATIONAL OPERATIONS: AN ELECTRONIC GATE SYSTEM INTEGRATING FACIAL RECOGNITION FOR ATTENDANCE TRACKING AND ACCESS CONTROL

article en
1 citations

Abstract

Efficient staff attendance management is a pivotal aspect of organizational success. The detrimental impact of poor staff attendance underscores the need for effective attendance monitoring methods. Automated approaches have emerged as solutions to mitigate the challenges associated with manual attendance tracking. From traditional paper-based methods to advanced technologies like radio frequency identification (RFID) and biometrics, the evolution of attendance monitoring techniques has significantly enhanced operational efficiency. Biometric-based attendance systems, leveraging unique physiological and behavioral attributes, have gained prominence due to their accuracy and security features. This study presents the development of an innovative electronic gate system employing facial recognition technology to regulate access and monitor staff attendance within organizational contexts. Facial recognition technology offers a balance between accuracy and privacy concerns, rendering it an ideal choice for identity verification applications. The proposed system utilizes strategically positioned cameras at access points to recognize staff members based on their facial features. A comprehensive database stores individual staff profiles, complete with associated images, facilitating seamless identification and attendance record-keeping. An integral facet of this system is the integration of an automatic penalization mechanism to deter tardiness. This mechanism deducts a predetermined amount from an employee's salary for each instance of punctuality violation. To address security vulnerabilities like tailgating, a weight verification feature has been incorporated to ensure that only authorized personnel gain access.

Zenodo (CERN European Organization for Nuclear Research)
Federal University of Technology Owerri (NG)
Openalex Percentile: Top 26%
Emotion and Mood Recognition
0.51
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