A Study on the Effectiveness of Smart Facial Recognition in Unlock Tools

In response to the evolving security landscape, this paper proposes an integration of facial recognition technology into door access control systems as a means to enhance security and convenience across diverse environments. By leveraging the trained VGG16 model, known for its precision in person identification, our model ensures accurate authentication of authorized individuals while deterring unauthorized access attempts. Notably, our approach allows for real-time expansion of the system’s database without extensive neural network retraining, thereby accelerating deployment and reducing associated costs. Additionally, we advocate for the integration of a basic anti-spoofing algorithm to fortify the model against fraudulent attempts, thereby enhancing its reliability and resilience. This research contributes to the advancement of access control technology by demonstrating the practicality and effectiveness of facial recognition models in door access scenarios, laying the groundwork for future exploration and innovation in this burgeoning field toward more secure and efficient access control systems.