neural network based solution for door automation - ieee.pdf (480.86 kB)
Download fileNeural Networks based solution for Door Automation
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.
History
Email Address of Submitting Author
monalika.6671@gmail.comSubmitting Author's Institution
Visvesvaraya Technological UniversitySubmitting Author's Country
- India