A Face Recognition Method In Machine Learning (ML) For Enhancing Security In Smart Home

The study explores with Machine learning (ML), which is a type of neural network (AI) that empowers software programmers to start increasing prediction without being done with full to make this happen Exterior door security is of paramount importance and has become the cornerstone for the best and fastest security or sufficient to choose a feeling of protection to property owners, and together with technological innovations, especially in the Communication area, which tends to make emerging innovations in locking doors or windows have picked up a lot, including such locking doors and windows with faces and the others. Face - recognition technologies have also been developed and used for residential door locking mechanisms, and they are a basic and easy-to-use technology that detects the features of homeowners quite well. The advancement of facial recognition has resulted in one of the computer vision algorithms that is simple to build and has a high accuracy in recognising faces, and it has been widely utilised. When consumers review or exposure to new goods, does this have an instant influence on your suggestion system or does it take time, How do suggestions evolve as consumers interact more with the platform, many different of each sort of recommendation system in order to have a more detailed of their capabilities.

I. Introduction

Among other things, in object classification systems In this survey, data is collected using the CNN Mobilenet biometric technology, which is installed in a waiting area locking mechanism, by collecting 742 biometric information on the face of the landlord using a system that is used to prepare algorithms, and the results are quite precise, with the correctness being approximately 97 percent, and that is quite high when compared to every other studies. In conclude, the CNN Alexnet technique can conduct highly good face recognition software and can be installed on an IoT device, notably the Raspberry Pi[1].