DESIGN AND DEVELOPMENT OF A FACIAL RECOGNITION ACCESS SYSTEM
Abstract
In an era where security remains a global priority, traditional access control systems are proving
inadequate against sophisticated intrusion methods. This project, therefore, focuses on the design
and development of a facial recognition access system to enhance security, convenience, and
automation in restricted environments. The aim is to leverage artificial intelligence, real-time facial
detection, and embedded systems to authenticate authorized users effectively and autonomously. The
system utilizes the ESP32 microcontroller, equipped with a camera module, integrated Wi-Fi, and a
relay- controlled door lock mechanism. A local web server facilitates face enrollment and
recognition processes, while a machine learning-based facial recognition algorithm performs realtime detection and authentication. Experimental results demonstrated the system's effectiveness in
identifying pre- registered users and rejecting unauthorized individuals with high accuracy. This
project concludes that facial recognition systems offer a reliable, scalable, and cost-effective
solution for modern access control
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