Facial Recognization Triple Security entryway system using AI & Deep Neural System

Abstract:

Security has always been a major concern for the households, offices & Bank system
environment, and for this concern, various approaches are in place to address the
problem. Most of the major Entryway lock security systems have several loopholes
which could be broken down to gain access to the desired places, and it creates a
concern for a secure lifestyle and proper working environment. Additionally, terrorism
and unauthorized access to places have become a major issue nowadays, and there is
a need for a secure system to prevent unauthorized access especially in shared access
environment.
With this consideration, design and prototype of a Triple Security Framework utilizing
facial acknowledgement, Passkey and knob pattern detection using Artificial Intelligence
and Deep Neural Network-based Door lock system has been presented in this project.
Triple Security framework such as facial acknowledgement, Passkey and knob pattern
detection mechanisms to enforce reliable logs of system transactions and protect an
individual’s right to privacy.
The RFID or password based door lock mechanisms can easily be compromised when
the RFID card or passwords are shared or stolen, thus for facilities with shared access
require Triple Layer Security system. In the proposed system, Face, Passkey & Knob
Pattern of the authorized users will be enrolled and verified to provide access to a
facility that is used by multiple users. A user can also be removed and a new user can
be enrolled in the system. We have implemented a centralized control system from
where we can control who can enter in which rooms and who cannot. This is the latest
Raspberry Pie device based flexible working device that provides physical security
using the various layers of security utilizing the Artificial and Deep Neural network.