Designing Of Web-Based Attendance and Class Scheduling System using RFID and Raspberry PI

Designing Of Web-Based Attendance and Class Scheduling System using RFID and Raspberry PI

Melvin S. Reyes , John Errol N. Caras

TTITCCR. 2023 June; 3(2): 1-8. Published online June 2023

Abstract : Cloud services have emerged as a promising solution to facilitate a wide array of heterogeneous activities, delivering highly efficient services in various domains. This study focuses on the design and implementation of a Web-Based Attendance and Class Scheduling System for Columban College, Inc. (CCI) located in Olongapo City, Philippines. The system integrates Radio-Frequency Identification (RFID) technology and Raspberry Pi to streamline attendance tracking and class scheduling processes. The proposed system aims to enhance the efficiency and accuracy of attendance monitoring while simplifying the class scheduling procedure for both students and faculty members. RFID technology is employed to facilitate quick and convenient attendance recording, eliminating manual methods, and reducing errors. Additionally, the Raspberry Pi serves as the central processing unit for data management and web-based access. The study presents a detailed analysis of system design, development, and implementation, highlighting the technical aspects of integrating RFID and Raspberry Pi into a web-based platform. The benefits of this system include real-time attendance updates, automated scheduling, and improved data management, contributing to enhanced productivity and transparency within CCI. By leveraging cloud services, this innovative system provides a scalable and efficient solution to address the unique challenges faced by educational institutions in managing attendance and class scheduling. The study underscores the potential of cloud-based technologies in revolutionizing administrative processes and improving overall educational experiences in institutions like Columban College, Inc. This project makes use of the following applications and technologies: RFID Reader, Raspberry Pi 4 Model B, Database Server, Bootstrap, PHP, and CSS.

Keyword : Attendance Monitoring, RFID reader, Raspberry Pi, RFID tags, Web-based, Reports.