International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue:10 | Oct 2024
p-ISSN: 2395-0072
www.irjet.net
Facial Recognition in Education: Conceptualizing 'Attendance Genie' for Automated Attendance Prof Vikas Gaikwad1, Vaishnavi Bilambe2, Sanika Patil3, Yashavant Patil4 , Diksha Waghale5 1
Professor, Department of Artificial Intelligence & Data Science, Shree Ramchandra College of Engineering, Pune, India *2*3*4*5 Student, Department of Artificial Intelligence & Data Science, Shree Ramchandra College of Engineering, Pune, India
---------------------------------------------------------------------***--------------------------------------------------------------------1. INTRODUCTION Abstract - This study introduces an automated attendance system that uses facial recognition technology to improve the efficiency and accuracy of attendance tracking. Developed on a Raspberry Pi, the system uses Python programming in conjunction with sophisticated image processing techniques and pattern recognition algorithms, such as convolutional neural networks (CNNs), to accurately detect facial features. The system uses the YOLOv8 (You Only Look Once version 8) model, which enables real-time object detection, allowing the system to quickly and accurately identify faces. By taking and analyzing facial images, the system recognizes and logs student attendance without the need for physical communication. In addition to reducing administrative work, this technology successfully stops proxy attendance, which occurs when a student signs in under a phony identity. Because the system operates in realtime, attendance is immediately recorded as soon as kids enter the classroom, cutting down on delays and freeing up teachers to concentrate on instruction rather than managing attendance. Furthermore, doing away with tangible inputs like sign-in papers encourages a contact-less method, which is crucial in the health-conscious world of today. SQL is used for data administration in order to provide effective storage and convenient access to attendance information. Using HTML, CSS, and JavaScript, the front end is constructed to provide administrators and teachers with an easy-to-use interface. This facial recognition attendance system is flexible and expandable for use in a variety of settings outside of the classroom, such as offices and conferences. In conclusion, it is a useful tool for efficient attendance management since it increases accuracy, decreases manual labor, and encourages active involvement.
Despite the modern world's advancements in technology, many educational institutions still maintain classroom attendance using antiquated techniques such manually calling out roll numbers or gathering student signatures. In addition to being time-consuming, these conventional approaches are prone to mistakes, including inaccurate data entry, absenteeism, and the prevalent problem of proxy attendance, in which one student indicates the presence of another. A more dependable and effective method of monitoring student attendance is essential, considering the strong correlation between attendance and academic achievement. As a result, educational institutions must use updated systems that simplify the attendance procedure and do away with the shortcomings of the current approaches. Advances in artificial intelligence (AI) and image processing have led to the emergence of facial recognition technology. Compared to other systems, face recognition, a biometric technology that recognizes people by examining their facial traits, has a number of benefits. Facial recognition is a more hygienic and long-lasting option than fingerprint scanners or RFIDbased systems because it doesn't require physical touch. Real-time, precise facial recognition, even with big datasets, is now possible thanks to recent advancements in AI and image processing technology, which makes it the perfect option for automating attendance in educational settings. The goal of this research is to create an automated attendance system that uses facial recognition technology to improve accuracy and efficiency. The system makes use of Python programming, the OpenCV library, and a Raspberry Pi, a low-cost and small single-board computer. A popular tool for real-time computer vision is OpenCV. As students enter the classroom, the system takes pictures of them, uses face recognition to identify them, and automatically records their attendance. Attendance is recorded automatically as soon as a student's face is identified. In educational settings, facial recognition technology has several benefits. First of all, it does away with the necessity of interacting physically with the system, which is extremely crucial for preserving hygiene,
Key Words: Convolutional Neural Networks (CNN), Raspberry Pi, facial recognition technology, automated attendance system, real-time object identification, SQL (Structured Query Language), YOLOv8 (You Only Look Once version 8), & User Interface.
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