License Plate Recognition-Based Automatic Gate Opening System

This study proposes an automatic electronic gate system that uses three main modules for authenticity confirmation: vehicle make and model, validation of license plate, and facial recognition. When a vehicle arrives at a gate or entrance, the system detects the vehicle, recognizes the license plate, and make and model, cross-references it with the database, and validates the driver's face against stored data. When there is a match, the Raspberry Pi signals the servo motor to open the gate; if not, an alert system is triggered. The proposed system is intended to improve security and convenience while decreasing the need for traditional access control measures such as stickers or security guards. Experimental results show that the system is capable of successfully identifying vehicles and number plate readings, with high precision and recall. The integration of several deep learning models, such as YOLO v7, YOLO v7-Tiny, and ResNet, contributes to the overall efficiency and performance of the system.