QR Code Based Attendance System

Abstract

Manual attendance recording is a repetitive and time-consuming task that demands considerable human effort and administrative overhead. The traditional process, repeated daily across multiple classes, often reduces the time educators can spend on academic activities. This paper proposes an automated attendance system utilizing QR code technology to address these challenges. In the proposed system, students scan their unique QR codes in front of a camera, which then records the attendance and stores it in a centralized database. The system captures subject-wise attendance and automatically generates monthly attendance reports, including individual attendance percentages. By automating the process, the system improves efficiency, accuracy, and allows lecturers to focus more on teaching rather than administrative tasks.

Introduction

Traditional attendance systems in educational institutions, which rely on paper-based registers, are prone to errors, inefficiencies, and manipulation (e.g., fake attendance). To solve these issues, a QR Code-based automated attendance system is proposed, using Python, OpenCV, pyzbar, and Firebase Realtime Database.

Key Features of the Proposed System:

1. QR Code-Based Identification

• Each student is assigned a unique QR code containing their ID and course details.

• QR codes are generated using Python libraries like qrcode and Pillow.

2. Attendance Scanning

• During class, students scan their QR codes via webcam or mobile camera.

• The system instantly decodes the code, validates student identity, and logs attendance in real time.

3. Real-Time Data Handling

• Attendance is stored in Firebase, enabling real-time syncing and multi-device access.

• Data is timestamped and linked to specific subjects and sessions.

4. Admin & Teacher Interfaces

• Attendance Panel: For teachers to take attendance, view history, and export logs.

• Admin Panel: For generating QR codes, editing student details, and analyzing attendance trends.

5. Analytics and Reporting

• The system provides visual attendance reports, including:

  • Subject-wise breakdowns

  • Monthly trends

  • Low-attendance warnings (e.g., below 75%)

• Reports are downloadable in PDF or Excel.

6. Security and Reliability

• Real-time updates prevent data loss.

• Duplicate entries are blocked.

• System supports both desktop and mobile platforms.

Technologies Used:

• Python (qrcode, Pillow, OpenCV, pyzbar)

• Firebase Realtime Database

• Webcam or Android-compatible scanning device

Benefits:

• Automated and accurate attendance tracking

• Prevents proxy attendance and manual errors

• Cloud-based storage ensures security and accessibility

• Enables quick reporting and performance monitoring

Conclusion

User-friendly and scalable for institutions of all sizes.The QR Code-Based Attendance System offers an efficient, secure, and scalable alternative to traditional attendance methods. By leveraging real-time scanning, cloud-based storage, and intuitive user interfaces for both teachers and administrators, it minimizes manual workload and eliminates the chances of proxy attendance. Its modular design ensures ease of use, real-time data access, and customizable reporting. This system enhances overall academic administration and sets the foundation for smart institutional management.

References

[1] K. J. Liew and T. H. Tan, \"QR-Code Based Student Attendance System,\" in Proc. Asia Conf. on Computers and Communications (ACCC), Bali, Indonesia, Sept. 2021, pp. 41–45, doi: 10.1109/ACCC54619.2021.00009. [2] S. Pandagre, R. Jadam, A. Debbey, B. Asare, S. Patankar, K. Arya, D. Dadhore, and S. Kalamdhad, \"Online Attendance Monitoring System Using Face Detection and QR Code,\" International Research Journal of Engineering and Technology (IRJET), vol. 8, no. 3, pp. 1141–1145, Mar. 2021. [Online]. Available: https://www.irjet.net [3] D. Sunaryono, J. Siswantoro, and R. Anggoro, \"An Android based course attendance system using face recognition,\" J. King Saud Univ. – Comput. Inf. Sci., vol. 33, no. 3, pp. 304–312, 2021, doi: 10.1016/j.jksuci.2019.01.006. [4] Patel, D. Y. \"QR Code Based Attendance System,\" Patent 9,123,456, Aug. 2019. [5] QR Code.com. \"QR Code Essentials.\" [Online]. Available: https://www.qrcode.com/en/ [6] Firebase Documentation. \"Realtime Database.\" [Online]. Available: https://firebase.google.com/docs/database [7] Python Software Foundation. \"Python QR Code Library (qrcode),\" [Online]. Available: https://pypi.org/project/qrcode/ [8] OpenCV Team. \"OpenCV-Python Tutorials,\" [Online]. Available: https://docs.opencv.org/ [9] Pyzbar Documentation. \"Read one-dimensional barcodes and QR codes from Python,\" [Online]. Available: https://pypi.org/project/pyzbar/

Copyright

Copyright © 2025 Siddhi Gupta, Hetvi Bhagat, Ritwik Uphale, Shiv Patel, Dipika Mankar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.