Abstract :

The Face Attendance System Using IoT And Face Recognition Is An Advanced Automated Solution Designed To Improve The Efficiency, Accuracy, And Security Of Attendance Management Systems In Educational Institutions And Organizations. Traditional Attendance Systems, Such As Manual Registers And ID Cardbased Methods, Are Prone To Errors, Timeconsuming, And Vulnerable To Proxy Attendance. These Limitations Necessitate The Development Of An Intelligent System Capable Of Automating The Attendance Process With Minimal Human Intervention. The Proposed System Utilizes Computer Vision And Machine Learning Techniques, Specifically Face Detection And Recognition, To Identify Individuals And Record Attendance In Real Time. The System Captures Facial Images Through A Camera Module And Processes Them Using OpenCV-based Algorithms. The Detected Faces Are Compared With Pre-stored Images In A Database To Verify Identity. Upon Successful Recognition, Attendance Is Automatically Recorded Along With Timestamp Information And Stored In An SQLite Database. The Integration Of IoT Enables Realtime Data Access And Monitoring Through A Webbased Interface Developed Using The Flask Framework. This System Ensures High Accuracy, Reduces Manual Effort, Eliminates Proxy Attendance, And Provides A Scalable Solution For Modern Attendance Management. Experimental Results Demonstrate That The System Achieves High Face Detection And Recognition Accuracy Under Varying Environmental Conditions. The Proposed System Is Cost-effective, User-friendly, And Adaptable For Deployment In Schools, Colleges, Offices, And Other Organizations. Furthermore, The System Supports Automated Report Generation And Real-time Tracking, Improving Administrative Efficiency. This Research Highlights The Potential Of Combining IoT And Artificial Intelligence Techniques To Develop Smart Attendance Systems That Enhance Reliability, Transparency, And Operational Effectiveness.

Published:

07-4-2026

Issue:

Vol. 26 No. 4 (2026)

Page Nos:

1396-1400

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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