This project presents a smart door lock system integrating face and voice recognition to enhance security and accessibility in home or office environments. The system leverages two microcontroller boards: Arduino Nicla for face detection using MobileNetv1 and Arduino Nano 33 for audio detection. Both models are trained and deployed through Edge Impulse. The face detection component identifies authorized users, while the audio detection module recognizes predefined voice commands. A solenoid lock mechanism was considered but presented power challenges due to the Arduino’s limited output capacity of 30mA versus the solenoid’s 1.5A requirement. The project emphasizes embedded machine learning, real-time inference, and energy-efficient design, offering a customizable, cost-effective alternative to commercial smart locks.
