The AI-Powered Smart Student Attendance Monitoring and Automation System is an intelligent classroom management solution that combines YOLO (You Only Look Once), OpenCV, Arduino Camera Module (ESP32-CAM/Arduino Camera), and RFID technology to automate student attendance and monitor classroom activities in real time.
The system uses an RFID reader to record attendance when students scan their RFID cards. Simultaneously, the Arduino camera module captures live classroom video, which is processed using OpenCV and the YOLO object detection model to detect, count, and track students. This ensures that the number of students present matches the attendance records and helps identify proxy attendance or unauthorized entries.
The system can continuously monitor classroom activities such as student presence, movement, and occupancy. Attendance records, monitoring data, and alerts are stored in a central database and displayed on a web dashboard for teachers and administrators. By integrating RFID authentication with AI-based computer vision, the system improves attendance accuracy, reduces manual effort, prevents fraudulent attendance, and enhances classroom discipline and security.
- Automate student attendance using RFID.
- Detect and count students using YOLO and OpenCV.
- Prevent proxy attendance.
- Monitor classroom occupancy in real time.
- Generate attendance reports automatically.
- Improve classroom security and management.
- YOLOv8/YOLOv11 – Real-time object detection
- OpenCV – Image processing and computer vision
- Python – AI and backend programming
- Arduino IDE – Programming the camera module
- ESP32-CAM / Arduino Camera Module – Live video streaming
- RFID (MFRC522) – Student identification and attendance
- PostgreSQL – Attendance database
- FastAPI – Backend API
- HTML, CSS, JavaScript – Web dashboard
- RFID-based automatic attendance
- AI-powered student detection and counting
- Real-time classroom monitoring
- Student tracking using YOLO
- Proxy attendance detection
- Live camera feed with object detection
- Attendance report generation
- Admin dashboard for monitoring
- Automated alerts for attendance mismatches
- Secure database storage
- Clone the repo
git clone https://github.com/NarwhalsOrg/VISTA.git- Install the packages
uv sync
If you not installed the uv install from UV installation Page.
- For running the app
uv run fastapi dev
- Want to run with docker
docker compose up --build
- Before pushing to the repo check formate and error
uv run ruff format .
uv tool run ruff check .
- Try auto fix if there is any problem
uv tool run ruff check . --fix
The proposed system provides a fast, accurate, and intelligent attendance management solution by integrating RFID authentication with computer vision. It minimizes manual work, improves attendance reliability, enhances classroom monitoring, and supports educational institutions in creating smarter and more secure classrooms.