Access Control Using Facial Recognition with Neural Networks for Restricted Zones

Abstract

: A new technology that has proven to be effective and accurate in identifying people today is facial recognition. This technology, when used with IP cameras, provides a very effective and practical access control system. Moreover, this system is able to learn and improve its facial recognition capability over time through the use of neural networks, leading to higher accuracy and a lower false positive rate in the field. Thus, this paper shows a face recognition system, based on neural networks, for monitoring and controlling access of people in small and medium-sized enterprises (SMEs); with the use of IP cameras for the versatility of continuous tracking to people circulating in restricted areas. On the other hand, common security problems that are identified in these environments are addressed and solutions are offered through the implementation of the proposed system. Finally, the results obtained demonstrate that the system offers an efficient and secure solution for monitoring and controlling access of people in restricted areas of small and medium-sized enterprises (SMEs). Its accurate identification capability, combined with the elimination of barriers and convenience for users, significantly improves security and user experience.