Development of Facial Recognition System for an Automatic Sliding Door

Security concerns, heightened by increasing incidents of robbery, theft, and other fraudulent
activities, necessitate more advanced access control systems. This project explores the development
of an automatic sliding door system integrated with facial recognition technology to enhance
security and accessibility. Utilizing a Raspberry Pi 4, the system incorporates a camera module to
capture and recognize facial images, allowing or denying access based on pre-registered data. The
system's design includes a DC motor to operate the door, a motor driver integrated circuit, and an
LCD for displaying operational status. The methodology involved the installation of the Raspbian
operating system on the Raspberry Pi, interfacing peripheral devices, and developing Python scripts
for facial recognition and motor control. The project addressed challenges such as power
dependency and camera sensitivity to environmental conditions. Testing confirmed the system's
ability to accurately identify authorized users and efficiently control door operations, demonstrating
80% recognition accuracy under varying facial expressions and lighting conditions. This project
contributes to the field of automated access control, offering practical insights into the integration
of facial recognition technology with everyday security mechanisms.