Abstract:
This paper presents a hybrid Internet of Things (IoT)-based attendance tracking system designed
to enhance the efficiency and accuracy of attendance management across educational institutions
and corporate environments. The primary objective of this research is to develop an automated
system that minimizes reliance on manual attendance processes while providing real-time
monitoring, reporting, and data analysis. Traditional attendance systems often face challenges such
as inaccuracies due to human error, buddy punching, time theft, and the significant administrative
burden of maintaining attendance records. These issues underscore the urgent need for a more
reliable and effective solution that can streamline the attendance process while ensuring
accountability.
To address these challenges, the proposed system integrates advanced technologies, including
biometric authentication through fingerprint recognition and Radio Frequency Identification
(RFID) technology. The methodology encompasses several key phases: first, the design of the
system architecture, which includes selecting appropriate hardware components such as RFID
readers and biometric scanners, will be undertaken. Next, a robust software application will be
developed to interface with these IoT devices, enabling real-time data collection, processing, and
user-friendly reporting features. The system will undergo rigorous testing in controlled
environments to ensure functionality, security, and user satisfaction. Feedback from initial users
will be incorporated to refine the interface and enhance overall usability.
Once the system has been validated, it will be deployed in real-world settings, such as schools and
workplaces, to gather live data and assess performance under actual operating conditions. The
expected findings suggest that the hybrid IoT-based attendance tracking system will significantly
reduce attendance errors and improve the efficiency of data management processes. By automating
attendance recording, the system is likely to minimize the risk of human error and increase the
accuracy of attendance records. Furthermore, real-time access to attendance data will enable timely
interventions when discrepancies occur, thereby improving accountability among users.
Ultimately, this hybrid system is anticipated to revolutionize attendance management by
addressing the limitations of conventional methods, leading to enhanced user experience,
improved productivity, and better resource allocation in various organizational contexts. Through
this research, we aim to contribute to the growing field of IoT applications by demonstrating the
potential of integrating biometric and RFID technologies for effective attendance tracking.
