An Intelligent Face Detection Attendance System with Real-Time Mobile Data Visualization
Authors: Imran Nazir, Shah Zaman Haider, Shanza Shafiq, Muhammad Amir Mushtaq, Umar Fayyaz
Abstract
With the increasing and fastest-growing need for diverse solutions in education and business environments, traditional and manual attendance systems are rapidly becoming outdated and time-consuming. Instead of using the manual method, this research introduces a new, advanced, IoT-based intelligent face detection attendance system using an ESP32 Cam with MicroPython programming that leverages computer vision, image processing, and machine learning to automate and secure attendance monitoring. By recognizing and verifying the face of an employee in real time, this system replaces manual input and eliminates the risk of proxy attendance. The record of attendance is instantly stored and displayed on a mobile device or web server through the ESP32 Cam module via a simple, user-friendly HTML interface, ensuring immediate access for both administrator and user. This real-time data visualization not only enhances transparency but also simplifies attendance management. The system represents a modern, advanced, efficient, reliable, and low-cost solution for organizations that saves time and effort and enables monitoring from anywhere.
