Introduction

Attendance tracking is a critical task in educational institutions and workplaces. Traditional methods such as manual registers or RFID-based systems are either time-consuming, error-prone, or susceptible to proxy entries. The Real-Time Attendance System Using Raspberry Pi provides a smart, automated, and contactless solution that leverages facial recognition technology to accurately record attendance.

This system is built using a Raspberry Pi, a Pi Camera, and facial recognition libraries like OpenCV and face_recognition. The camera captures the faces of individuals in front of the system, matches them against a pre-trained database of known faces, and automatically marks attendance with timestamps. This approach improves accuracy, eliminates manual work, and ensures a secure and real-time way of maintaining attendance records.

Working Principle

The system operates by capturing real-time images of individuals standing in front of the camera using the Raspberry Pi Camera module. These images are processed using facial recognition algorithms to extract unique facial features (encodings). The encodings are then compared against a database of pre-stored face encodings.

If a match is found, the individual's name and timestamp are recorded in an attendance log. The entire process is managed locally by the Raspberry Pi, making it an efficient edge-computing solution that does not require continuous internet access. The attendance data can be saved in a CSV file or a local database for easy retrieval and analysis.

Methodology

1. Image Capture and Preprocessing

   • The Pi Camera captures real-time video or images of individuals.

   • Frames are resized and converted to RGB format for processing.

2. Face Detection and Encoding

   • Using libraries like face_recognition and OpenCV, the system detects faces in the frame.

   • It extracts 128-dimensional facial encodings for each detected face.

3. Face Matching

   • The system compares the live face encoding against a known database of encodings.

   • If a match is found within a defined accuracy threshold, the name is identified.

4. Attendance Logging

   • Once identified, the name and timestamp are stored in an attendance file (CSV or database).

   • Duplicate entries for the same day are avoided using logic checks.

5. Real-Time Output

   • The system displays the name and status (e.g., “Present”) on the screen and logs the data.