Facial recognition system for borrowing equipment
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Abstract
This project proposes the development of a smart borrowing and returning cabinet system using Raspberry Pi integrated with infrared sensor and a facial recognition system. The system designs to identify the users through facial recognition before granting access to borrow or return equipment. The cabinet operation has simple two states: when the user’s face successfully verified the cabinet unlocks; otherwise, the access is denied. The cabinet shows the status through the LED, if there is an equipment in the cabinet, the light will be on. But if there is no equipment, the light will be off. All borrowing and returning activities are logged in a .txt file to recording the student ID, date, and time. The face recognition methodology is recognizing the user faces without any face covering like hats, glasses, masks, etc. and record in database as reference. The evaluates from 3 volunteers. The results show all samples the face recognition system can be verified when users no face covering. In case of wearing sunglasses, hats or masks or have some covering the face, the system will lower performance. In addition, if another person who does not store information, the system cannot verify as designed.
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