Implementation of Face Recognition in People Monitoring Access In-and-Out of Crystal Dormitory Universitas Klabat

Abstract

Crystal Dormitory is a dormitory in Universitas Klabat that accommodates some male students. This study aims for monitoring and minimize the entry of foreigners into the dormitory which affects the comfort and safety of boarding students. Using the prototyping model, the systems can observe the faces of students who live in the dormitory, as well as foreigners who enter the dormitory. The system performed face recognition to recognize a person’s face when the person’s face data has been stored in the dataset. The hardware in this system used a Raspberry Pi 3 which is integrated with a webcam and monitor to detect and recognize human facial images. With machine learning libraries namely TensorFlow, OpenCV, Dlib, and Haar Cascade, combine with Python programming, the system can detect and recognize human facial images. If the system detects an unfamiliar human face, then the image of that person's face will be sent via the Telegram application using the auto-send feature to notify about the unidentified person.