Development of an IoT-Based Biometric Attendance Management System

In educational institutions and business organizations, efficient attendance recording and monitoring are essential. Traditional manual methods are complex, time-consuming, and inaccurate, allowing impersonation and lacking data availability for analysis. IoT technology offers a solution through smart attendance systems, but most of the existing solutions are not scalable and cannot handle extensive data processing and storage requirements efficiently. Additionally, biometric accuracy and reliability need improvement. Hence, this work presents an IoT-based biometric attendance management system using a Node Microcontroller Unit (NodeMCU), an Inter-Integrated Circuit (I2C), a Liquid Crystal Display (LCD), a fingerprint sensor, and a power supply. It features an interactive graphical user interface (GUI) accessible via Android devices or laptops, enabling remote monitoring and reporting through a web application. Tested with multiple students, the system showed ease of implementation, high security, time savings, and improved accuracy and reliability over traditional methods. Key contributions include automatic attendance management and a comparative analysis against existing techniques using metrics such as power consumption, security, speed, cost, functionalities and portability. The system captures and verifies fingerprints in approximately 4 seconds, operates on minimal power (5V), and is cost-effective with locally sourced components. It ensures secure and reliable attendance tracking, eliminating proxy attendance and manual errors by storing data in the cloud.