Study and Application of ESP32 facial detection smart door simulator for security

Abstract

This research to present the study and research on developing a smart door system utilizing facial recognition for security purposes have been conducted by a team of researchers who designed an efficient authentication system. This system utilizes the ESP32 microcontroller to control door unlocking mechanisms and integrates multiple authentication methods including RFID tag scanning, fingerprint scanning via sensors, and the use of a TFT LCD screen for password input, ensuring proper authorization before door access. Additionally, an option to incorporate ESP32-CAM with a motion detection sensor (HC-SR50) is available to capture images of individuals approaching the door, with notifications sent through LINE Notify. The system's performance was evaluated with a sample group of 30 individuals, resulting in high satisfaction levels, with a mean satisfaction score of 4.56 and a standard deviation (S.D.) of 0.69. These findings demonstrate that the developed smart door system aligns with project objectives and exhibits the anticipated effectiveness and completeness. This research has the potential for broad application, such as in security systems for buildings, workplaces, or public places. Improving the authentication system to record effectively and store data could enhance security and reduce the risk of unauthorized access. Developing the system to include various functions and connectivity with other IoT technologies would also facilitate convenient and efficient usage.