Smart Home Security Solutions using Facial Authentication and Speaker Recognition through Artificial Neural Networks

In this paper, a holistic solution for Smart Home Security is implemented which helps in improving privacy and security using two independent and emerging technologies of facial authentication and speech recognition. With the help of the proposed application, the user will be able to monitor his home through his mobile phone/tablet/PC. This method involves facial recognition by taking a real-time feed of the person at the door and then analysis of the live feed is carried out where the face recognised is authenticated with the data of owners in the database which matches the face to a name. Speech recognition has been used to doubly check the output of facial authentication. The entire process is carried out with the help of neural networks. If there's an unauthorized person at the door, an alert will be triggered and the owner will get a notification of this unauthorized access and would get to choose whether they want to add the person to their database or not. The overall accuracy of the proposed model is 82.71% with an accuracy of 87.5 % for Facial Authentication and 84.62 % for Speaker Authentication. Along with this, the main novelty for the research is to identify faces through masks which will help to properly verify the identity of the person and would prove to be beneficial not only in the current COVID-19 scenario but also in cases of thefts and burglaries by alerting the owner about the anomaly. Thus this smart security system can be extended to applications like banks, malls, offices, etc., and shall not be limited to only homes