Automated access control systems have been widely used in recent years due to their high accuracy and security. In this study, we present an intelligent and secure electronic gate based on facial recognition and vehicle number plate recognition. The system combines multimodal biometric technology with face recognition using the 'face_recognition' package and automatic licence plate recognition (ALPR) using YOLOv8 and PaddleOCR to enhance the security of access to restricted areas. The system was able to correctly recognise 29 out of 30 faces, while all licence plates were accurately recognised, even at different times. The results show that the automated gate system has been successfully developed and tested with an accuracy rate of 96.67%. This success demonstrates the potential use of multimodal biometric technology to improve the security and efficiency of access control systems in various applications, such as office environments, residential areas and other public facilities. Further research can be directed towards improving the resilience of the system to different environmental conditions and expanding the database of recognised faces and vehicle number plates.
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