ANALYSIS, DESIGN AND IMPLEMENTATION A HYBRID IOT-BASED ATTENDANCE TRACKING SYSTEM A CASE STUDY: ULK GISENYI CAMPUS

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.