Paper Contents
Abstract
The student attendance system is a web application that utilizes face recognition, machine learning, Redis, Python, and Streamlit to automate and enhance the process of recording and managing student attendance in educational institutions. Traditional attendance methods, such as manual roll call or barcode scanning, are time-consuming, error-prone, and often suffer from attendance fraud. This web application offers a reliable and efficient solution by leveraging face recognition technology.The system utilizes machine learning algorithms to train a face recognition model capable of identifying students accurately. This model is integrated into the web app, which provides an intuitive and user-friendly interface for administrators and teachers to manage attendance records. By capturing real-time images of students through webcams or mobile devices, the system matches the faces with the stored database of registered students and records their attendance automatically.To ensure scalability and efficient storage of student information, Redis, an in-memory data structure store, is utilized as a fast and reliable database system. Redis allows for quick retrieval and manipulation of attendance records, providing real-time updates and analytics. Python's extensive libraries and frameworks, such as OpenCV and TensorFlow, enable seamless integration of face recognition capabilities.Streamlit, a powerful web application framework, is employed to create an interactive and visually appealing user interface. With Streamlit, administrators and teachers can access attendance reports, generate insights, and perform administrative tasks with ease.The student attendance system web app offers numerous benefits, including accurate attendance tracking, reduced administrative burden, increased efficiency, and improved transparency. By leveraging face recognition, machine learning, Redis, Python, and Streamlit , this system presents a comprehensive solution to enhance the attendance management process in educational institutions, ultimately contributing to improved academic outcomes and streamlined administrative operations.
Copyright
Copyright © 2023 Sharvari Basarkar. This is an open access article distributed under the Creative Commons Attribution License.
