Admin Controlled Automatic Smart Attendance Recognition System

Python-based facial recognition system for automated, subject-wise student attendance tracking using computer vision algorithms to enhance accuracy and efficiency.

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📖 Project Overlook

1. Admin User Interface
2. Data managed by MySQL database
3. OpenCV Frontalface Algorithm for recognition
4. Timetable-based Attendance Management

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📝 Project Brief

This project is designed to ease faculty workload and automate attendance tracking using a timetable-based approach.

Key Highlights:

• Built with Python (Tkinter GUI), ESP32-CAM, and ILI9341 display
• Uses MySQL database for secure and scalable data management
• Attendance is automatically recorded within the first 10 minutes of each lecture
• Absent students are marked automatically if not detected in that window
• OpenCV with LBP Histogram ensures accurate facial recognition
• Admins have full control to add new users, manage timetable, and monitor attendance

Hardware Integration

• ESP32-CAM: low-power camera module with Wi-Fi, Bluetooth, and microSD support
• ILI9341 TFT Display: used for user-friendly display output
• Arduino Board: connects and manages hardware components

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🚀 Features

• Fully automated smart attendance system
• Subject-wise and timetable-aware attendance
• Easy admin management for users & schedules
• Accurate recognition using OpenCV + LBP Histogram
• Scalable for schools, offices, and institutions

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🛠️ Tech Stack

• Python (Tkinter GUI)
• OpenCV (Facial Recognition)
• MySQL (Database & Authentication)
• ESP32-CAM + Arduino
• ILI9341 Display

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📦 Setup Instructions

Prerequisites

• Python >= 3.8
• MySQL Server installed
• ESP32-CAM + Arduino IDE configured

Installation

git clone https://github.com/theankitdash/Smart-Attendance-System.git
cd Smart-Attendance-System
pip install -r requirements.txt