AN AI-POWERED FACIAL RECOGNITION SYSTEM FOR AUTOMATED STUDENT IDENTIFICATION AND ATTENDANCE MANAGEMENT

It should be noted that there is a need to implement a highly effective student identification systemwithin educational institutions, demonstrating how ineffective traditional attendance systems can be,such as physical registers or ID cards.Within this paper, we suggest a new system of student identification that uses artificial intelligencetechnologies and has the potential to transform existing student attendance systems. The new studentidentification system that we propose uses artificial intelligence, specifically computer vision ormachine learning technologies, to identify student faces through the use of cameras.Our proposed student identification system has been developed using artificial intelligence technology,particularly computer vision or machine learning technology to recognize the faces of students usingcameras. Our proposed student identification system has been developed using programminglanguages such as Python or OpenCV with the aid of other enabling technologies like machinelearning algorithms or database management systems.Our proposed student identification system has proven its efficiency through experimental outcomesusing artificial intelligence technology. Our proposed student identification system marks an importantmilestone in the advancement of smart education through artificial intelligence technology

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-06
DOI
https://doi.org/10.5281/zenodo.19439813
Primary Topic
AI and Multimedia in Education
Type
article
Field-Weighted Citation Impact
0.00
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article

AN AI-POWERED FACIAL RECOGNITION SYSTEM FOR AUTOMATED STUDENT IDENTIFICATION AND ATTENDANCE MANAGEMENT

Himani Sharma, Smriti Verma, Harsh Yadav and Sanjana Varyani
Zenodo (CERN European Organization for Nuclear Research)
AI and Multimedia in Education
article

AN AI-POWERED FACIAL RECOGNITION SYSTEM FOR AUTOMATED STUDENT IDENTIFICATION AND ATTENDANCE MANAGEMENT

Himani Sharma, Smriti Verma, Harsh Yadav and Sanjana Varyani
article en

Abstract

It should be noted that there is a need to implement a highly effective student identification systemwithin educational institutions, demonstrating how ineffective traditional attendance systems can be,such as physical registers or ID cards.Within this paper, we suggest a new system of student identification that uses artificial intelligencetechnologies and has the potential to transform existing student attendance systems. The new studentidentification system that we propose uses artificial intelligence, specifically computer vision ormachine learning technologies, to identify student faces through the use of cameras.Our proposed student identification system has been developed using artificial intelligence technology,particularly computer vision or machine learning technology to recognize the faces of students usingcameras. Our proposed student identification system has been developed using programminglanguages such as Python or OpenCV with the aid of other enabling technologies like machinelearning algorithms or database management systems.Our proposed student identification system has proven its efficiency through experimental outcomesusing artificial intelligence technology. Our proposed student identification system marks an importantmilestone in the advancement of smart education through artificial intelligence technology

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 5%
AI and Multimedia in Education
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AN AI-POWERED FACIAL RECOGNITION SYSTEM FOR AUTOMATED STUDENT IDENTIFICATION AND ATTENDANCE MANAGEMENT — Himani Sharma, Smriti Verma, Harsh Yadav and Sanjana Varyani · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS