Electronic Door App Development Using Machine Learning And Face ID

Abstract

Face recognition technology (Face ID) has emerged as a highly secure solution by leveraging the distinctive attributes of each individual.  The application of Face ID in electronic door access systems significantly enhances security across residential, commercial, and public facilities.  This research's urgency can markedly enhance access security relative to traditional approaches and intelligent, secure, and efficient security solutions.  The objective of the research is to create a Face ID-based door security system, enhancing efficiency and reliability in access security.  The research employs the experimental technique alongside system development utilising the waterfall model.  The process involves analysing requirements to facilitate research, followed by system design, system testing, and concluding with system implementation.  Face ID employs artificial intelligence and machine learning technology to identify registered faces.  The precision of facial detection with a high-resolution camera and its connection with a smart lock may be managed via the application. A biometric authentication system utilizing facial recognition can serve as a substitute for traditional door lock mechanisms. The main components of the electronic door include biometric recognition based on Face ID. Its mechanism uses a solenoid lock to automatically control the door lock through electromagnetic action. The user interface is equipped with an LCD screen, which displays comprehensive information about the status of the electronic door.  The testing findings indicate that the input and output hardware of the system, specifically the camera and servo motor, function effectively.