Abstract
Face Recognition is one of the most common biometric strategies which
has gained popularity because of the accuracy and security. This paper
presents the implementation of a Convolution Neural Network architecture
for door automation. This model is devised to overcome the disadvantages
of a traditional door system and other methods such as door automation
using Bluetooth, figure prints, passwords, or retinal scans. It allows
the authorized people to gain access to the house by face recognition.
The proposed system makes use of convolution neural network
architectures and RaspberryPi. The ResNet architecture [6] is used
to implement face recognition and runs on RaspberryPi. The images of the
residents of the house will be used to train the model. If the person is
a resident of the house, the face will be recognized and the lock will
open, else it will be recognized as a human and an alarm will ring and
an email alert consisting of the image of the person in front of the
door will be sent to the owner. It has numerous advantages as it is
user-friendly especially for senior citizens, lesser maintenance, does
not require the residents to carry the keys and reduces the threat of
robbery.