RFID-Based Smart Attendance Management Systems Using IoT and Cloud Platforms

Abstract

Nowadays, attendance management is a very essential task in educational institutions, but traditional manual methods like registers or simple digital sheets are time-consuming, and the chances of getting errors increase. The common problems are proxy attendance, data loss, and record maintenance. There has been so much research done on automated attendance systems in the last few years to solve these problems. This review paper presents a detailed study on RFID-based attendance management systems using the Internet of Things (IoT) and cloud platforms. The paper analyses existing research works, which include RFID, biometric, QR code, and cloud-based attendance systems. The advantages, limitations, and challenges of different approaches are compared. Along with this, the areas of research gaps and future improvement are identified. This review paper gives a clear direction to understand current trends and future research of automated attendance systems.

Introduction

Traditional attendance systems in schools and workplaces are inefficient, time-consuming, and prone to errors such as proxy attendance and data loss. To address these issues, the text proposes an automated attendance management system based on RFID technology integrated with IoT and cloud computing. This system uses RFID tags/cards, microcontrollers like Arduino or ESP32, and cloud platforms such as Firebase or AWS to enable real-time, contactless attendance tracking and storage.

RFID technology works by wirelessly reading unique tag IDs without line-of-sight, making it faster and more reliable than manual or barcode-based systems. When a tag is scanned, the microcontroller processes the data and sends it to the cloud for storage and instant access. Studies show that RFID-based systems can significantly reduce recording time, improve accuracy (up to ~99%), and eliminate proxy attendance, especially in large-scale environments.

The literature review highlights several related approaches, including biometric systems, QR code-based systems, and cloud-based platforms. While biometrics offer high accuracy, they are costly and raise privacy concerns. QR code systems are low-cost and scalable but depend on smartphones and internet access. Cloud-based systems improve accessibility and real-time monitoring but require strong connectivity and raise data security concerns. Compared to these, RFID-based IoT systems provide a balanced solution with good accuracy, low cost, and ease of deployment, though challenges like proxy card misuse and internet dependency still exist.

Conclusion

In this review paper, a detailed analysis of automated attendance management systems has been done, which mainly focuses on the study of RFID-based systems with IoT and cloud technology. It is cleared from the literature review. Traditional manual attendance methods like roll call and registers are time-consuming, and the chances of proxy attendance, data loss, and human errors are higher. Automated systems like RFID, biometric, QR code, and cloud-based attendance solutions solve these problems to a better extent. RFID-based attendance systems are low-cost and easy to use, and when integrated with IoT, real-time storage and real-time monitoring are possible. But using RFID only shows some limitations, like proxy attendance through card swapping, hardware dependency, internet requirements, and data security issues. It was also noticed in reviews that most of the research is limited to the prototype level, with very little real-world large-scale implementation. Future research should focus on hybrid systems like RFID, which should be used with face recognition or biometrics or better encryption techniques and AI-based analytics. These systems make attendance management more secure, scalable, and intelligent

References

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Copyright

Copyright © 2026 Kusum Kumari, Goutam Shaw, Debosmita Sukul, Anurima Majumdar, Antara Ghosal. 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.