Smart Fingerprint Attendance System Using Raspberry Pi

Volume: 11 | Issue: 02 | Year 2025 | Subscription
International Journal of Embedded Systems and Emerging Technologies
Received Date: 04/06/2026
Acceptance Date: 07/03/2026
Published On: 2026-01-31
First Page: 20
Last Page: 27

Journal Menu


By: RutujaR Margaje, SakshiB Gaikwad, MA Tamhare, and Rutuja RPol.

1-3 Student, Shri Chhatrapati Shivajiraje College Of Engineering, Dhangawadi, Pune.
4- Professor, Shri Chhatrapati Shivajiraje College Of Engineering, Dhangawadi, Pune.

Abstract

This paper presents the design and implementation of a smart fingerprint-based attendance system tailored for classroom environments. The system uses a Raspberry Pi 3 A+, a fingerprint sensor, and Google Sheets for automatic, real-time logging of student attendance. The system offers an efficient, secure, and user-friendly solution to track student attendance while minimizing errors associated with traditional manual methods. It eliminates the need for paper-based attendance management and integrates seamlessly with cloud-based storage, providing access to attendance data from any device with internet access.

Fingerprint Authentication, Raspberry Pi 3 A+, Classroom Attendance, Google Sheets, Automation, Cloud Storage.

Loading

Citation:

How to cite this article: RutujaR Margaje, SakshiB Gaikwad, MA Tamhare, and Rutuja RPol Smart Fingerprint Attendance System Using Raspberry Pi. International Journal of Embedded Systems and Emerging Technologies. 2025; 11(02): 20-27p.

How to cite this URL: RutujaR Margaje, SakshiB Gaikwad, MA Tamhare, and Rutuja RPol, Smart Fingerprint Attendance System Using Raspberry Pi. International Journal of Embedded Systems and Emerging Technologies. 2025; 11(02): 20-27p. Available from:https://journalspub.com/publication/ijeset/article=23047

Refrences:

1. Joice A, Tufaique T, Tazeen H, Igathinathane C, Zhang Z, Whippo C, Hendrickson J, Archer D. Applications of Raspberry Pi for Precision Agriculture—A Systematic Review. Agriculture. 2025 Jan 21;15(3):227.
2. Singh J. Applied Data Science and Smart Systems. Goyal SB, Kaushal RK, Kumar N, Sehra SS, editors. Taylor & Francis Group; 2024 Jul 22.
3. Kumar M, Agarwal A, Pradhan SR. Fingerprint-based biometric authentication for educational attendance systems. Int J Comput Sci Technol. 2024 Jan;9(1):14-20.
4. Gupta RD. Raspberry Pi for IoT-based educational systems. Int J Educ Technol. 2022 Mar;12(3):56-60.
5. Google Developers. Google Sheets API [Internet]. Mountain View (CA): Google; [cited 2025 Mar 7]. Available from: https://developers.google.com/sheets/api
6. Wazwaz A, Amin K, Semary N, Ghanem T. Dynamic and distributed intelligence over smart devices, Internet of Things edges, and cloud computing for human activity recognition using wearable sensors. J Sens Actuator Netw. 2024 Jan 2;13(1):5.
7. Badawi AA. Internet of Things (IoT): origins, embedded technologies, smart applications, and its growth in the last decade. 2024.
8. Yalli JS, Hasan MH, Badawi AA. Internet of Things (IoT): origins, embedded technologies, smart applications, and its growth in the last decade. IEEE Access. 2024 Jun 24;12:91357-82.
9. Badshah A, Ghani A, Daud A, Jalal A, Bilal M, Crowcroft J. Towards smart education through internet of things: A survey. ACM Computing Surveys. 2023 Sep 14;56(2):1-33.

10. Witczak D, Szymoniak S. Review of monitoring and control systems based on Internet of Things. Applied Sciences. 2024 Oct 4;14(19):8943.