International Journal of Science, Engineering and TechnologyAuthors: Yash Chudgar, Karan Chauhan, Prutha Patel, Adityasinh Jadav, Dr. Nitin Mishra (Mentor)
Abstract: The rise of biometric technologies has transformed how identity is managed and authenticated in digital systems. Among these, facial recognition has emerged as a leading solution for contactless, efficient, and secure identity verification. This paper presents a review of a web-based vision identity system that integrates facial recognition with modular service provisioning using machine learning. Users register their identity via facial data, and based on their preferences, gain access to tailored services such as automated attendance logging, photo sorting by face, access control to secure spaces, visitor tracking, and real- time identity verification. The backend system utilizes advanced facial recognition models trained on curated datasets, while the frontend provides user and administrator panels to manage interactions. This review outlines the technical architecture, machine learning methodology, real-world use cases, and the potential challenges such as privacy concerns and environmental limitations. The paper highlights the system’s scalability, rele- vance across sectors, and its implications for the future of web- integrated identity systems.
DOI: https://doi.org/10.5281/zenodo.17090262
