Abstract
Security of house doors is very important and becomes the basis for the simplest and easiest security and sufficient to provide a sense of security to homeowners and along with technological developments, especially in the IoT field, which makes technological developments in locking house doors have developed a lot like locking house doors with faces and others. The development of facial recognition systems has also developed and has been implemented for home door locking systems and is an option that is quite simple and easy to use and is quite accurate in recognizing the face of homeowners. The development of the CNN method in facial recognition has become one of the face recognition systems that are easy to implement and have good accuracy in recognizing faces and has been used in object recognition systems and others. In this study, using the CNN Alexnet facial recognition system which is implemented in a door locking system, data collection is done by collecting 1048 facial data on the face of the homeowner using a system which is then used to train machine learning where the results are quite accurate where the accuracy is the result is 97.5% which is quite good compared to some other studies. The conclusion is the CNN Alexnet method can perform facial recognition which is quite accurate which can be implemented on the IoT device, namely, the Raspberry Pi.
Highlights
Over the past few years, there have been quite a several choices in conventional technology and biometric technology to meet security needs for households or offices
In the journal [4] facial recognition as authentication is very good because the face is a physiological feature that is easiest to distinguish between individuals so face recognition is one of the biometrics technologies that are often studied and developed
We propose a facial recognition process for the process of opening the door of a house that can replace the process of home security using an electronic key or RFID, where the research stages are divided into 3 parts, namely the stages of collecting homeowner data, the data training process, and the facial recognition process using Raspberry Pi
Summary
Over the past few years, there have been quite a several choices in conventional technology and biometric technology to meet security needs for households or offices. The previous paper described a prototype of a safe room access control system based on facial recognition This system consists of a webcam to detect faces and a solenoid door lock to access the room. The Haar cascade classifier embedded in OpenCV can recognize multiple captured images [7] Another project is designing facial recognition systems for smart home/office security applications. Where the results of the accuracy measurement based on the test table carried out three times get a success rate of 71.40%, 85.71%, 71.42% [9] and In another study, a door security system was developed using facial recognition as a key to open doors.
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