Face Recognition Door Lock System Using Arduino

The level of security can be raised by using face detection.

Face recognition door lock system using arduino.

Before diving into the code let s connect the solenoid lock with the raspberry pi. An alexa enabled door lock with face recognition and remote control. This will signal the arduino to unlock the door. We ll discuss the arduino code and circuit design later in this.

Similarly for unlocking we ll write low value to d0 and high value to d3. In today s tutorial we will learn how to build the face recognition door lock system using raspberry pi this project consists of three phases. Face detection and data gathering. The esp32 cam can host a video streaming web server over wi fi with very good fps frames per second which we can access with any device from our network.

The following block diagram can helps for better understanding. Block diagram of secured room access system controlling unit door lock door lock. Lock closed as the face does not matched. The project will consist of three phases.

Face recognition technology has improved drastically in the past decade and now it is primarily used for surveillance and security purpose. I hope you like this smart home project using esp32 cam board. You can also subscribe to our newsletter to receive more such useful electronics projects through email. Raspberry pi receives this command and sends to arduino using serial port.

This will signal the arduino to lock the door. Arduino control the lock accordingly. For locking we use the digitalmultiwrite method from library to write high value to d0 and low value to d3. If the face does not match with the enrolled face the door will remain lock as you can see in the above picture.

Block diagram of the system. In this project i will show you how you can create a facial recognition system by building an ip surveillance cctv with the esp32 cam module. In the existing system we are using password based door lock system which makes the user memorize password all the time. So to overcome this drawback we designing a new system with face recognition.