International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 11 | Nov 2025
p-ISSN: 2395-0072
www.irjet.net
Smart Attendance: An AI-Based Web System for Automated Attendance Management Riyaj Mulla1, Akshay Managave2, Santosh Dugane3, Sammed Badde4, Mrs.P.P.Mane5 Department of Computer Engineering, Sharad Institute of Technology, College of Engineering, Yadrav, Maharashtra, India ---------------------------------------------------------------------***--------------------------------------------------------------------1.1 Need for Automation Abstract - This paper presents the design and implementation of Smart Attendance, an automated attendance management system that uses artificial intelligence and facial recognition. The system identifies students in real time through a webcam and marks attendance automatically without manual effort. A webbased interface allows teachers to view, edit, and download daily reports, while all data are stored securely in a centralized database. The system reduces human error, saves time, and provides accurate tracking of attendance. Experimental use in a classroom environment showed that the proposed approach achieves high recognition accuracy and simplifies the overall process of attendance monitoring.
Manual attendance tracking leads to inefficiency and inaccuracy. Teachers spend a considerable amount of lecture time marking attendance, which reduces effective teaching hours. Smart systems using artificial intelligence can automate this repetitive process and improve accuracy andconvenience.
1.2 Objective of the System The objective of the Smart Attendance system is to minimize manual effort, ensure real-time attendance marking, and maintain secure digital records. It also aims to provide a web-based dashboard for teachers to view, edit, and download reports easily.
Key Words: Attendance system, facial recognition, web application, artificial intelligence, automation, database management
2. Methodology / System Design
1.INTRODUCTION
The Smart Attendance system follows a modular architecture consisting of four major parts: face detection and recognition, database management, web interface, and reporting. The system uses a laptop or external webcam to capture live images of students. Faces are detected using the OpenCV library and encoded through a deep learningbased recognition model. Each face is matched with stored records in the database, and attendance is marked automatically once the match is confirmed. The frontend of the web application is built using HTML, CSS, and JavaScript to create a user-friendly interface. The backend is developed in Python using the Flask framework, while MySQL is used for secure data storage. Teachers can log in to check attendance statistics, generate reports, and export data in Excel format. The system also includes an admin module for managing student records. The Smart Attendance workflow begins when the camera captures live images of the classroom. The captured image is processed by the recognition module that extracts facial features using a pretrained deep learning model. These features are compared with stored encodings of registered students. Once a match is found, the student’s ID and timestamp are recorded automatically in the database. In case of multiple faces, the system handles recognition sequentially to ensure every student is marked only once.
Attendance plays an important role in educational institutions as it reflects student participation and discipline. Traditional attendance methods such as roll calls or manual registers are time-consuming, prone to mistakes, and difficult to maintain. With increasing digitalization, there is a growing demand for smart systems that can automate this routine task. Smart Attendance is developed to overcome these issues by applying artificial intelligence and face recognition technology. The system captures a student’s face image, verifies identity with the existing database, and records attendance automatically. The collected data can be viewed online by teachers and administrators through a simple web interface. The main goal of this work is to save time, ensure accuracy, and minimize manual effort in the attendance process. With the introduction of modern technologies such as artificial intelligence and machine learning, it has become possible to automate repetitive academic tasks efficiently. The Smart Attendance system aims to combine face recognition, web-based user interaction, and secure data handling in one unified platform. It not only helps in daily record maintenance but also supports teachers by automatically generating attendance summaries and reducing paperwork. The use of web technologies makes the system portable and accessible from any device within the network.
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