Visible to the public Image Processing Technique for Smart Home Security Based On the Principal Component Analysis (PCA) Methods

TitleImage Processing Technique for Smart Home Security Based On the Principal Component Analysis (PCA) Methods
Publication TypeConference Paper
Year of Publication2020
AuthorsRizki, R. P., Hamidi, E. A. Z., Kamelia, L., Sururie, R. W.
Conference Name2020 6th International Conference on Wireless and Telematics (ICWT)
Keywordsactuator security, actuators, buzzer, composability, Databases, Face detection, face recognition, home automation, Human Behavior, image processing technique, Metrics, microcontrollers, OpenCV, PCA, principal component analysis, Principal Component Analysis method, pubcrawl, Python software, Raspberry Pi, Raspberry pi 3 microcontroller, Resiliency, security, security system, smart home security, Smart homes, solenoid door lock actuator, test data, webcam camera, Webcams
AbstractSmart home is one application of the pervasive computing branch of science. Three categories of smart homes, namely comfort, healthcare, and security. The security system is a part of smart home technology that is very important because the intensity of crime is increasing, especially in residential areas. The system will detect the face by the webcam camera if the user enters the correct password. Face recognition will be processed by the Raspberry pi 3 microcontroller with the Principal Component Analysis method using OpenCV and Python software which has outputs, namely actuators in the form of a solenoid lock door and buzzer. The test results show that the webcam can perform face detection when the password input is successful, then the buzzer actuator can turn on when the database does not match the data taken by the webcam or the test data and the solenoid door lock actuator can run if the database matches the test data taken by the sensor. webcam. The mean response time of face detection is 1.35 seconds.
Citation Keyrizki_image_2020