Access Control Using Facial Recognition with Neural Networks for Restricted Zones

Rodrigo Reaño, Piero Carrión, Juan-Pablo Mansilla

2023

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.

Paper Citation

in Harvard Style

Reaño R., Carrión P. and Mansilla J. (2023). Access Control Using Facial Recognition with Neural Networks for Restricted Zones. In Proceedings of the 19th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST; ISBN 978-989-758-672-9, SciTePress, pages 310-318. DOI: 10.5220/0012185800003584

in Bibtex Style

@conference{webist23,
author={Rodrigo Reaño and Piero Carrión and Juan-Pablo Mansilla},
title={Access Control Using Facial Recognition with Neural Networks for Restricted Zones},
booktitle={Proceedings of the 19th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST},
year={2023},
pages={310-318},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012185800003584},
isbn={978-989-758-672-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST
TI - Access Control Using Facial Recognition with Neural Networks for Restricted Zones
SN - 978-989-758-672-9
AU - Reaño R.
AU - Carrión P.
AU - Mansilla J.
PY - 2023
SP - 310
EP - 318
DO - 10.5220/0012185800003584
PB - SciTePress