An RFID-based Smart Attendance System built with Arduino Uno and Python that automates student attendance recording while preventing duplicate registrations and unauthorized access.
The NFS Attendance System combines embedded hardware with desktop software to create an efficient attendance management solution.
Students register attendance by scanning their RFID cards. The system instantly validates the card, provides visual and audio feedback, and stores attendance records in a CSV file through serial communication between Arduino and Python.
- RFID-based student identification
- Automatic attendance registration
- Prevents duplicate attendance entries
- Detects unknown RFID cards
- Green/Red LED status indicators
- Buzzer notifications
- LCD display for real-time messages
- Automatic CSV attendance logging
- Timestamp generation
- Python serial communication
- Easy integration with Microsoft Excel
- Power on the Arduino system.
- Scan an RFID card.
- The system checks whether the UID is registered.
- If the student is valid:
- Green LED turns on.
- Buzzer beeps once.
- LCD displays a welcome message.
- Attendance is recorded.
- If the student has already registered:
- Red LED turns on.
- Buzzer beeps twice.
- LCD displays Already Present.
- If an unknown card is scanned:
- Red LED turns on.
- Buzzer alerts.
- LCD displays Unknown Card.
- Python receives the attendance data and stores it in attendance_log.csv.
- Arduino Uno
- MFRC522 RFID Module
- RFID Cards / Tags
- 16x2 I2C LCD
- Green LED
- Red LED
- Buzzer
- Breadboard
- Jumper Wires
- C++
- SPI Library
- MFRC522 Library
- Wire Library
- LiquidCrystal_I2C
- Python 3
- PySerial
- CSV
- OS
- Datetime
NFS-Attendance/
│
├── NFS Attendance.cpp
├── attendance_log.csv
├── README.md
├── LICENSE
└── Project Photos/
Each attendance record includes:
| Field | Description |
|---|---|
| UID | RFID Card ID |
| Name | Student Name |
| Date & Time | Attendance Timestamp |
| Status | Present |
- Database integration (MySQL / SQLite)
- Cloud synchronization
- Web Dashboard
- Mobile Application
- Face Recognition
- Fingerprint Authentication
- Email Notifications
- Attendance Analytics
Mohamed AlBry
Faculty of Computer Science & Artificial Intelligence
This project is licensed under the MIT License.