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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Willy Andika Putra
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Implementasi Sistem Otomatisasi Pintu Dengan Face Recognition Menggunakan Metode Haar-Cascade Dan Local Binary Pattern Pada Raspberry Pi Willy Andika Putra; Rizal Maulana; Fitri Utaminingrum
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Technological developments in the world are starting towards the IOT (Inthernet Of Things) era. Smarthome is one of IOT Technology whose the impact is felt by many people. Smarthome is an embedded dwelling of many integrated technologies and make almost aspects in the home run automatically. One aspect that needs to be considered in the smarthome is the security aspect, all the smarthome integrated residence should has a very adequate security system. The security system owned by smarthome is mostly implemented on the door, for example implanting a sensor on the door to keep the door locked automatically. However, there will be many obstacles when using sensor technology, one of them is most sensors can not identify someone who is near the door. From the problem will be made an open door automation system on smarthome that can identify someone. The identification technology that will be used in the system is Face Recognition using Haar-Cascade method which will be implemented on single-board circuit that is Raspberry Pi. The system will store the identity of the Smarthome inhabitants in a dataset and will open the door if the data matches with the previously created dataset. Face Recognition will use Library Open CV that is Haarcascade_Frontal_Face and cv2.createLBPHFaceRecognizer . The level of detection accuracy using haarcascade classifier method is 76.25% while for the level of accuracy of introduction used local binary pattern is equal to 65%. To Connect face recognition with open door closing system, the author uses 3 pieces of DC motor. Two DC motors as Door Wheels and 1 DC motor as a key. All process will be done by Self Process on Raspberry.
Co-Authors Rizal Maulana Utaminingrum, Fitri