Rancang Bangun Sistem Gerbang Otomatis dengan Pengenalan Wajah dan IoT Berbasis Android

Abstract

The rapid development of Internet of Things (IoT) technology and facial recognition systems has opened significant opportunities for enhancing smart security systems in residential, office, and industrial environments. However, conventional gate systems that rely on manual keys or remote controls remain inefficient and vulnerable to duplication, loss, and delayed access. This study aims to design and develop an automatic gate system equipped with facial recognition using the Eigenface method, integrated with IoT technology and an Android-based application. The Eigenface method applies the Principal Component Analysis (PCA) approach to extract unique facial features by generating eigenvectors that represent facial characteristics. Facial recognition is performed by comparing the user’s eigenface values with those stored in the system’s database, while real-time data communication between hardware and the Android application is facilitated through an ESP8266 microcontroller and Firebase cloud services. System testing was conducted on five users under three different lighting conditions (bright, dim, and nighttime) to evaluate recognition accuracy, response time, and IoT communication stability. The results show that the system achieved an average facial recognition accuracy of 93.4% under normal lighting, 89.1% under dim lighting, and 85.7% at night, with an average system response time of 10 seconds from detection to gate opening. The IoT connection demonstrated 98% communication reliability over standard home Wi-Fi networks. These findings indicate that the proposed automatic gate system successfully enhances security, operational efficiency, and user convenience, providing an innovative and intelligent solution for modern remote-access security applications.