DEVELOPMENT OF FACIAL RECOGNITION SYSTEM FOR AN AUTOMATIC SLIDING DOOR
Abstract
This report presents the development of a facial recognition-based automatic sliding door system aimed at enhancing security and accessibility. The primary objective is to design an efficient and contactless access control system that ensures secure entry for authorized individuals while restricting unauthorized access. The problem statement highlights the increasing demand for smart security systems due to rising security concerns and accessibility challenges faced by individuals with disabilities. The methodology involves integrating a Raspberry Pi 4 with a camera module to capture and recognize facial images. The system also includes a motor driver and a DC motor to operate the sliding door. The installation of the Raspbian Operating System, interfacing with peripheral devices, and the development of Python scripts for facial recognition and motor control are key components of the system implementation. Testing was conducted to evaluate facial recognition accuracy, response time, system reliability, and privacy compliance. The results indicate that the system effectively identifies authorized individuals and responds within an average time of 15 seconds, demonstrating efficiency and reliability. In conclusion, this project successfully implements a facial recognition-based access control system for automatic sliding doors. Future enhancements may include IoT integration for remote access, multifactor authentication for added security, and further optimization of the recognition algorithm to improve accuracy under varying environmental conditions.
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