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A Smart University Gate Using Face Recognition and IoT |
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PP: 1113-1128 |
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doi:10.18576/amis/190512
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Author(s) |
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Lama Al Khuzayem,
Ohoud Alzamzami,
Shahad Bamani,
Jawahirah Alsafari,
Abeer Hadadi,
Aseel Alshahrani,
Hajar Alharbi,
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Abstract |
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| Smart security integrates innovative technology and intelligent systems to improve the safety and protection of organizations. Due to the increased populations around the world, the adoption of smart solutions for securing university premises is becoming increasingly important as the number of students and staff who use these premises is constantly increasing. Thus, the goal of this paper is to implement a smart university gate system that allows students to use either their university cards or face IDs for authorization. Our proposed solution comprises two integral components, namely a website and a smart gate system. The website serves as a platform for administrators to register new students or staff members by collecting their personal information and capturing their images. The smart gate system utilizes deep learning and machine learning techniques, specifically ResNet50 with Logistic Regression, for detecting and recognizing faces. A real-time face recognition model is deployed on a Raspberry Pi 4, which is connected to an administrator’s computer via a cloud connection. The Raspberry Pi is also connected to a camera, a screen, and an Arduino microcontroller through a serial connection. The Arduino microcontroller is linked to a barcode scanner and a servo motor. It controls the gate based on the results from the face recognition model or the barcode scanner. The system facilitates a smooth entry of students, faculty, and staff to the university campus, ensuring a safer and more efficient environment.
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