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@article{187625,
        author = {Mimansha Singh and Foram Shah and Hetal Rana and Akshata Raut},
        title = {A Real-Time Face Recognition-Based Automated Attendance System Using OpenCV},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {5983-5990},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187625},
        abstract = {This project introduces an innovative Face Detection Attendance System designed to modernize and replace outdated methods of tracking attendance in various sectors. Traditional attendance methods, such as manual check-ins or card-based systems, are prone to errors, delays, and even manipulation. Our proposed system leverages advanced computer vision technology and machine learning algorithms to automate the attendance process by detecting and identifying individuals based on their facial features. The system operates seamlessly by using an on-board camera to capture real-time facial images. These images are then compared against a pre-stored database containing the facial profiles of enrolled individuals, such as students or employees. Once an individual is identified, the system automatically logs their attendance in real-time. This information is Instantly updated and made accessible to supervisors or administrators, ensuring transparency and eliminating delays in attendance reporting. Our system is built on a robust architecture that ensures high accuracy even in challenging scenarios, such as changes in lighting conditions or when only a portion of a face is visible due to obstructions like masks or accessories. Additionally, the system incorporates analytics tools that allow for comprehensive attendance data analysis. These insights can help supervisors address recurring attendance issues and make data- driven decisions for better management. The Face Detection Attendance System offers several key advantages. It minimizes the risk of human error and eliminates the possibility of self-service duplication or proxy attendance. It also enhances security by preventing unauthorized access and ensuring that only registered individuals can interact with the system. By automating the attendance process, this system saves significant time, reduces administrative overhead, and delivers accurate results efficiently. The potential applications of this system extend beyond education to corporate environments, healthcare facilities, and other industries where accurate attendance tracking is critical. By adopting this modern solution, organizations can improve productivity, enhance accountability, and streamline operations. In essence, the Face Detection Attendance System is a transformative technology that offers a futuristic approach to attendance management with far-reaching implications for a wide range of sectors.},
        keywords = {Face detection attendance system, Facial recognition, Attendance automation, Proxy attendance prevention},
        month = {November},
        }