Introduction
Smart home security has evolved far beyond traditional locks and keys. In this project, we build a face recognition-based door lock system using the ESP32-CAM module. This system identifies authorized individuals and unlocks the door automatically—no keys, no cards, just your face.
The ESP32-CAM is a powerful yet affordable microcontroller with a built-in camera, making it ideal for IoT-based vision applications. Combined with its onboard Wi-Fi, it enables real-time face detection and recognition directly from a web interface.
How the System Works
The system captures live video using the ESP32-CAM and processes it to detect and recognize faces. Once a face is recognized, the microcontroller triggers a relay module to unlock the door.
Here’s the flow:
- The camera captures a live video stream.
- Faces are detected in the frame.
- The system compares detected faces with stored data.
- If a match is found, the door unlocks.
- If not, access is denied.
All of this happens in real time through a browser-based interface.
Components Required
- ESP32-CAM module
- FTDI programmer (for uploading code)
- Relay module
- Solenoid lock or electronic door lock
- Jumper wires
- Power supply
Circuit Overview
The ESP32-CAM connects to a relay module that controls the door lock. The relay acts as a switch—when triggered, it powers the lock mechanism to open the door.
Since the ESP32-CAM has limited GPIO pins, careful pin selection is required. Typically, one GPIO pin is used to control the relay.
Setting Up the ESP32-CAM
1. Arduino IDE Configuration
- Install the ESP32 board package in Arduino IDE.
- Select the correct board: AI Thinker ESP32-CAM.
- Choose the correct COM port.
2. Uploading the Code
- Connect the ESP32-CAM to the FTDI programmer.
- Set GPIO 0 to GND to enable programming mode.
- Upload the face recognition example code.
- Remove GPIO 0 from GND after uploading.
Face Detection and Recognition
The ESP32-CAM supports:
- Face detection
- Face enrollment
- Face recognition
Enrolling Faces
Using the web interface:
- Open the IP address of the ESP32-CAM in a browser.
- Enable face detection and recognition.
- Capture multiple images of a person to train the system.
Recognition Process
Once trained, the system compares live images with stored facial data. If a match is found, it triggers the relay.
Web Interface Features
The ESP32-CAM hosts a simple web server that allows you to:
- View live video feed
- Enable/disable face detection
- Enroll new faces
- Control recognition settings
This makes the system easy to manage without additional apps.
Door Lock Integration
When a face is successfully recognized:
- The ESP32-CAM sends a signal to the relay
- The relay activates the solenoid lock
- The door unlocks for a few seconds
- Then it automatically locks again
You can adjust the unlock duration in the code.
Power Considerations
The ESP32-CAM requires a stable 5V supply. Insufficient power can cause:
- Camera failures
- Random resets
- Wi-Fi instability
Using a dedicated power source is recommended for reliable operation.
Enhancements You Can Add
To make the system more robust:
- Add a buzzer for alerts
- Integrate a mobile notification system
- Store logs of recognized faces
- Use a battery backup
- Add infrared LEDs for night vision
Final Thoughts
This ESP32-CAM Face Recognition Door Lock System demonstrates how accessible and powerful embedded AI has become. With just a single module, you can build a complete smart security system capable of recognizing faces in real time.
Whether you're exploring IoT, home automation, or computer vision, this project is a great way to combine all three into a practical application. Explore hands-on IoT builds and tutorials in this comprehensive collection of ESP32 projects with code and circuit diagrams to kickstart your next embedded systems idea
If you're looking to expand it further, consider integrating cloud storage or combining it with other smart home systems for a fully automated experience.
Top comments (0)