Integrating Machine Learning and Software Development in a Web-Based Face Recognition Attendance System

A robust system designed to authenticate individuals and record attendance using facial recognition technology powered by deep learning. This project simplifies attendance tracking for classrooms, workplaces, or events.

Features

• Role-based access for administrators, lecturers.
• Manage courses, units, venues, and attendance records through an intuitive interface.
• Capture and store multiple images for accurate identification.

Technologies Used

Frontend:

• HTML – Structure of the web pages
• JavaScript – Client-side interactivity
• Bootstrap – Frontend Framework

Backend:

• PHP – Server-side scripting language
• MySQL – Database management system

Additional Tools:

• Face-api.js – Face recognition library
• Fetch API/AJAX – Handling asynchronous requests
• SweetAlert2 - A customizable JavaScript library for beautiful, responsive alert boxes.

Team

• Christian Andrei T. Arzadon (Lead Developer)
• Jann Gio Tabios (UI/UX Developer)
• Fritzjerald L. Domingo (Documentation Lead)
• Carl Dominic Doño (Team Leader)

Project Structure

User Interface