2-Factor-Authentication-and-IoT-based-Smart-Attendance-System-for-Institutions-and-Workplaces

IoT-based system for attendance by merging 2FA security with facial recognition. Requires both a physical face scan and a dynamic OTP, eliminates buddy punching. Designed for institutions, provides real-time, cloud-synced data and mobile-integrated management, ensuring a seamless, secure, and fully auditable attendance process for all workplaces.

This Smart Attendance System leverages IoT hardware and computer vision to provide a secure, automated solution for institutions and workplaces. It eliminates manual errors and "buddy punching" by requiring two-factor verification: a physical face scan and a time-sensitive OTP.

---

System Overview

• Location-Locked Security: Attendance is restricted exclusively to the classroom environment; the system is configured to work only on the designated class network, ensuring that users must be physically present to sign in.
• Facial Recognition: Automatically detects and matches faces against a registered database.
• 2FA Security: Requires a secondary OTP verification via a dedicated web app for every attendance entry.
• Admin Dashboard: A mobile-responsive web panel to manage class counts, monitor attendance in real-time, and perform administrative "undo" actions.
• Cloud Synchronization: Integrates with Firebase to ensure data availability across devices.
• Automated Reporting: Sends personalized attendance summaries via Gmail API.

---

Getting Started

1. Prerequisites

Ensure you have Python 3.13+ installed and a Raspberry Pi (or Linux machine) with a connected camera.

sudo apt update
sudo apt install python3-venv sqlite3 -y

2. Environment Setup

# Clone your project and enter directory
git clone https://github.com/ishaanparikh14/2-Factor-Authentication-and-IoT-based-Smart-Attendance-System-for-Institutions-and-Workplaces.git
cd 2-Factor-Authentication-and-IoT-based-Smart-Attendance-System-for-Institutions-and-Workplaces

# Create and activate virtual environment
python3 -m venv venv
source venv/bin/activate

# Install dependencies
pip install flask google-api-python-client google-auth-httplib2 google-auth-oauthlib opencv-python firebase-admin requests

3. Database Initialization

The system creates the attendance.db automatically on first run. To ensure a fresh start:

# Remove old DB to force a fresh schema creation
rm attendance.db

4. Model Configuration

The ArcFace model is not included due to size limits. Initialize it automatically:

python3 download_models.py

5. Configuring Credentials

Place your credentials.json (for Gmail/Firebase APIs) in the /home/pi/face_attendance/ folder. Ensure your GMAIL_SENDER email is updated in email_service.py.

6. Running the System

You must run the two core components simultaneously in separate terminal sessions:

Terminal 1: Start the Web/Admin Server

source venv/bin/activate
python app.py
# The web interface is available at http://<PI_IP>:5000 (accessible only via class Wi-Fi)

Terminal 2: Start the Attendance/Camera Loop

source venv/bin/activate
python main.py

Architectural Workflow

1. Network Validation: The system validates the request source; attendance requests from outside the local class network are automatically rejected.
2. Detection: main.py processes live camera frames.
3. Verification: Upon a face match, the user is prompted to enter an OTP from the web app.
4. Sync: attendance_db.py updates the local SQLite store, triggers the email report, and pushes the final data to Firebase.
5. Admin Review: The lecturer uses the /admin route to manage total sessions and view real-time statistics.

For troubleshooting, ensure your Raspberry Pi is connected to the same local network as the students' devices, and verify that the credentials.json has the correct gmail.send scope permissions.