Implementasi Sistem Keamanan Rumah (SMARTHOME) Berbasis Internet Of Things Dengan Metode Eigenface
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Institusion
Institut Teknologi Telkom Purwokerto
Author
Alfisyah, Prisianda Pangestu Utomo
Subject
T Technology (General)
Datestamp
2022-03-21 08:42:59
Abstract :
Every human being has a need for security to protect himself from threats that can befall at any time. One implementation to meet these needs is to build a house. Besides being used as a shelter, the house is also a means of social activities for family members. But in reality the house is targeted by a few people to commit crimes. Over time the creation of CCTV to record the state of the house, but the use of CCTV is still considered weak. This is what motivated the author to create an IoT-based home security system with the eigenface method. This study aims to determine the effectiveness of the use of a home security system in providing home security. This research develops a home security system using IoT-based devices and applies facial recognition. The IoT-based device uses a Raspberry Pi 3b+ and a raspberry camera. The application of face recognition uses the eigenface algorithm with PCA and SVM as classifications. Monitoring results can be accessed through the website with the flask framework. The system can open the door manually and automatically with the face recognition process. System testing with as many as 5 people who were tested directly got an accuracy of 90.5% by going through 30 tests on each person. Keywords: Raspberry Pi, Internet of Things, Principal Component Analysis, Support Vector Machine, Flask
Every human being has a need for security to protect himself from threats that can befall at any time. One implementation to meet these needs is to build a house. Besides being used as a shelter, the house is also a means of social activities for family members. But in reality the house is targeted by a few people to commit crimes. Over time the creation of CCTV to record the state of the house, but the use of CCTV is still considered weak. This is what motivated the author to create an IoT-based home security system with the eigenface method. This study aims to determine the effectiveness of the use of a home security system in providing home security. This research develops a home security system using IoT-based devices and applies facial recognition. The IoT-based device uses a Raspberry Pi 3b+ and a raspberry camera. The application of face recognition uses the eigenface algorithm with PCA and SVM as classifications. Monitoring results can be accessed through the website with the flask framework. The system can open the door manually and automatically with the face recognition process. System testing with as many as 5 people who were tested directly got an accuracy of 90.5% by going through 30 tests on each person. Keywords: Raspberry Pi, Internet of Things, Principal Component Analysis, Support Vector Machine, Flask
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