Design and Simulation of a Face Recognition-Based Smart Door Lock Using Python and OpenCV

Keys, access cards and PIN codes can be misplaced, duplicated or handed to others, and an ordinary lock offers the owner no means of judging a person who has not been registered. This paper proposes a software-simulated smart door lock that admits registered people through face recognition and forwards every unregistered visitor to the owner for a decision. A webcam provides live frames to a Haar Cascade detector. Each face found is normalised and compared with a stored set of enrolled people by the Local Binary Patterns Histograms (LBPH) recognizer in OpenCV, and a distance threshold separates familiar faces from strangers. An enrolled person opens a virtual door at once. For a stranger, the program sends the captured image to the owner’s Telegram bot together with Allow and Deny buttons, and the door opens only after Allow is pressed; Deny, silence or any fault leaves it locked. All events are recorded in a time-stamped log. The prototype runs in Python on an ordinary laptop, so no Raspberry Pi board or lock hardware is required during testing, while the modular code can later drive a relay. The paper explains the architecture, algorithms, parameter choices, security considerations, expected strengths and weaknesses, and a structured test plan. No measured accuracy is reported, because the prototype has not yet been evaluated.