RFID-Based Attendance System with Camera Screen

Abstract

This paper proposes a dual-authentication-based smart attendance system, integrating Radio Frequency Identification (RFID) with an ESP32-CAM image capture module. Conventional attendance systems, which work on manual entry or RFID single-factor authentication methods, are subjected to proxy manipulation and human error. The proposed attendance system verifies the attendance of individuals at two stages. At the first stage, RFID tags attached to the users are scanned; simultaneously, a live face image is captured. In parallel to the process flow, at the instant of scanning, the RFID UID is read by Arduino Uno, which is then reflected for instant feedback onto the LCD, buzzer, and LED indicators. Simultaneously, ESP32-CAM captures the user image, encodes it in base64 format, and sends it with the user’s unique identifier (UID) to the MySQL database using the XAMPP local server. The model was implemented in real environments and recorded high accuracy, fast authentication, and reliable image logging. The designed model is cost-effective, scalable, and meant for educational institutions and workplaces where safeguarded attendance tracking is needed.

Introduction

Traditional paper-based attendance is prone to errors and proxy marking, while biometric systems face hygiene and speed issues. RFID systems offer quick, contactless attendance but cannot prevent misuse when cards are shared. To overcome these limitations, the proposed system combines RFID identification with ESP32-CAM live face capture for secure, dual-factor authentication.

Literature Review

Previous studies explored attendance automation using:

• Biometrics (fingerprints, face recognition) for identity verification.

• RFID for fast, contactless marking.

• Hybrid systems combining RFID and facial recognition for added security.
  However, low-cost real-time systems integrating RFID with live image capture using ESP32-CAM were lacking.

System Architecture

• Hardware: Arduino Uno, RC522 RFID reader, ESP32-CAM, LCD display, LEDs, buzzer.

• Software: Arduino IDE, ESP32 firmware, PHP, MySQL, XAMPP.

• Process: Users enroll RFID UID and reference face image; attendance is marked by reading UID and capturing a live image, which is stored with timestamp in MySQL. Admins monitor attendance via a web dashboard.

Results

• Successful dual authentication with 98% accuracy.

• Average response time <2 seconds.

• Errors occurred due to poor lighting or incorrect camera angle.

• MySQL database effectively stored user details, images, and timestamps for easy retrieval and monitoring.

Conclusion

The given study demonstrates that the integration of RFID identification and live face capture with ESP32-CAM offers a secure, efficient, and low-cost solution for managing attendance. The system has shown ample potential in overcoming the drawbacks presented by both traditional and biometric methods while offering dual authentication, real-time data storage, and ease of usage. These results support the efficiency and suitability of the design to be deployed within schools, colleges, offices, and secure premises. Future research could aim at cloud deployment, mobile application-based authentication, and AI-driven face recognition to improve performance.

References

[1] G. Al-Muhaidhri and J. Hussain, “Smart Attendance System Using Face Recognition,” IJERT, 2019. [2] M. Olagunju et al., “Fingerprint-Based Staff Attendance Monitoring System,” IJCA, 2018. [3] M. Ula et al., “RFID-Based Student Attendance Tracking,” JPCS, 2021. [4] K. Bhatti et al., “Face Recognition-Based Attendance Management,” EAI Publications, 2019. [5] S. R. Sruthi et al., “RFID and Face Recognition-Based Secure Attendance System,” IRJMETS, 2022.

Copyright

Copyright © 2025 Nitin Chavan, Arnold James, Md Sameer Ahmed, Tipu Sultan, Prof. Pratik Shankar. 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.