Pengembangan Sistem Kunci Pintu Otomatis Berbasis ESP8266 Menggunakan CCTV Rumah dan Algoritma Multi-Task Cascade Convolutional Neural Network untuk Identifikasi Pemilik Rumah

Abstract

One of the primary challenges in home security management is ensuring that access is granted only to legitimate residents. To address this issue, a system is developed to automatically recognize the faces of registered occupants using Multi-Task Cascade Convolutional Neural Network (MTCNN) algorithms. Integration with home CCTV enables the system to monitor and process images of users approaching the door, thereby enhancing accuracy in identification. Additionally, the intelligent automatic door solution is expected to provide additional protection for the home and its occupants, minimizing the risk of unauthorized access and instilling greater confidence in residents. Beyond improving security, the system aims to enhance the convenience of accessing the home, offering greater flexibility and ease in managing home security for residents. By leveraging affordable and accessible technologies such as ESP8266 and home CCTV, the development of an ESP8266-based automatic door system using home CCTV and MTCNN algorithms for owner identification is anticipated to offer an efficient, cost-effective, and reliable solution to enhance overall home security and convenience.