ESP32-CAM Face Recognition Door Lock System (2023) (2023)

Security is at most concern for anyone nowadays, whether it's data security or security of their own home. With the advancement of technology and the increasing use of IoT, digital door locks have become very common these days. Digital lock doesn’t require any physical key but it uses RFID, fingerprint, Face ID, pin, passwords, etc. to control the door lock. In past, we have developed many digital door locks applications using these various technologies. In this tutorial webuild a Face ID controlled Digital Door lock system using ESP32-CAM.

The AI-Thinker ESP32-CAM module is a low-cost development board with a very small size OV2640 camera and a micro SD card slot. It has an ESP32 S chip with built-in Wi-Fiand Bluetooth connectivity, with 2 high-performance 32-bit LX6 CPUs, 7-stage pipeline architecture. We have previously explained ESP32-CAM in detail and used it to build a Wi-Fi door Video doorbell. This time we will use the ESP32-CAM to build a Face Recognition based Door Lock System using a Relay module and Solenoid Lock.

Components Required

  • ESP32 CAM
  • FTDI Board
  • Relay Module
  • Solenoid Lock
  • Jumper Wires

Solenoid Lock

A solenoid lock works on the electronic-mechanical locking mechanism. This type of lock has a slug with a slanted cut and a good mounting bracket. When the power is applied, DC creates a magnetic field that moves the slug inside and keeps the door in the unlocked position. The slug will retain its position until the power is removed. When the power is disconnected, the slug moves outside and locks the door. It doesn’t use any power in a locked state. To drive the solenoid lock, you would need a power source that can give 12V @ 500mA.

ESP32-CAM Face Recognition Door Lock System (2023) (1)

We previously used a solenoid lock to build an Arduino based RFID door lock.

Circuit Diagram

The Circuit Diagram for ESP32-CAM Face Recognition Door Lock System is given below:

The circuit above combined with an FTDI board, Relay Module, and Solenoid Lock. The FTDI board is used to flash the code into ESP32-CAM as it doesn’t have a USB connector while the relay module is used to switch the Solenoid lock on or off.VCC and GND pins of theFTDI board and Relay module is connected to the Vcc and GND pin of ESP32-CAM. TX and RX of theFTDI board are connected to RX and TX of ESP32 and the IN pin of the relay module is connected to IO4 of ESP32-CAM.


FTDI Board



(Video) ESP32 CAM Face Detection Door Lock System








Relay Module





(Video) ESP32 CAM Face Recognition Door Lock System



Note: Before uploading the code, connect the IO0 to the ground. IO0 determines whether the ESP32 is in flashing mode or not. When GPIO 0 is connected to GND, the ESP32 is in flashing mode.

After connecting the hardware according to the circuit diagram, it should look something like below:

ESP32-CAM Face Recognition Door Lock System (2023) (2)

Install ESP32 Board on Arduino IDE

Here Arduino IDE is used to program ESP32-CAM. For that, first, install the ESP32 add-on on Arduino IDE.

To install the ESP32 board in your Arduino IDE, go to File> Preferences.

ESP32-CAM Face Recognition Door Lock System (2023) (3)

Now copy the below link and paste it into the “Additional Board Manager URLs” field as shown in the figure below. Then, click the “OK” button:

ESP32-CAM Face Recognition Door Lock System (2023) (4)

Now go to Tools > Board > Boards Manager

(Video) esp32 cam face detection door lock system #esp32cam #arduinoprojects

(Video) face recognition based door lock using esp32 cam.

ESP32-CAM Face Recognition Door Lock System (2023) (5)

In Board Manager, search for ESP32 and install the “ESP32 by Espressif Systems“.

ESP32-CAM Face Recognition Door Lock System (2023) (6)

Code Explanation

Weexplained Face Recognition with ESP32 in the previous article; here we will modify the same code to control a solenoid door lock. The complete code is divided into four parts. One is the main code for the camera and relay module where the ESP32 locks or unlock the door according to face recognition, and the other three codes are for web page, camera index, and camera pins. Complete code is given at the end of this page. Here we are explaining some important parts of the code.

Begin the program by including all the library files.

#include "esp_camera.h"#include <WiFi.h>#include "camera_pins.h"

In the next line,uncomment the camera module that you are using with ESP32. In the code, five different camera models are defined. In this case, we’re using the AI-THINKER Model.


After that, insert your network credentials in the following variables:

const char* ssid = "Wi-Fi Name";const char* password = "Wi-Fi password";

Then define the pin where the relay module is connected. We will be using millis() function to lock the door after unlocking it in a defined interval of time, here it is 5 seconds.

#define relay 4long prevMillis = 0;int interval = 5000;

In the setup() function, initialize the Serial Monitor at a baud rate of 115200 for debugging purposes. Then in the next lines, define the pin mode for the relay module and also set the relay at a low position initially.

void setup() { Serial.begin(115200); pinMode(relay, OUTPUT); digitalWrite(relay, LOW);

Inside the loop() function, check if the face matches with the enrolled face. If yes, then unlock the door for 5 seconds and after 5 seconds lock the door again.

void loop() { if (matchFace == true && activeRelay == false){ activeRelay = true; digitalWrite (relay, HIGH); prevMillis = millis(); } if(activeRelay == true && millis()- prevMillis > interval){ activeRelay = false; matchFace = false; digitalWrite(relay, LOW); }

Testing the ESP32-CAM Face Recognition Door Lock System

Finally to upload the code, connect the FDTI board to your laptop, and select the ‘ESP32 Wrover Module’ as your board. Also, change the other settings as shown in the below picture:

ESP32-CAM Face Recognition Door Lock System (2023) (7)

(Video) ESP32-CAM Face Recognition Open Door Lock

(Video) ESP32 Cam Door lock & Bell 🔔 | Blynk Door lock & Bell System @ARRoboTics

Don’t forget to connect the IO0 pin to GND before uploading the code and also press the ESP32 reset button and then click on the upload button.

Note: If you get errors while uploading the code, check that IO0 is connected to GND, and you selected the right settings in the Tools menu.

After uploading the code, remove the IO0 and GND pin. Then open the serial monitor and change the baud rate to 115200. After that, press the ESP32 reset button, it will print the ESP IP address and port no. on the serial monitor.

ESP32-CAM Face Recognition Door Lock System (2023) (8)

Now navigate to the browser and enter the ESP IP address that is copied from the Serial monitor to access the camera streaming. It will take you to the streaming page. To start the video streaming, click on the ‘Start Stream’ button at the bottom of the page.

ESP32-CAM Face Recognition Door Lock System (2023) (9)

To recognize the faces with ESP32-CAM, first, we have to enroll the faces. For that, turn on the Face recognition and detection features from settings and then click on the Enroll Face button. It takes several attempts to save the face. After saving the face, it detects the face as subject 0 where zero is the face number.

ESP32-CAM Face Recognition Door Lock System (2023) (10)

After enrolling the faces, if a face is recognized in the video feed, ESP32 will make the relay module high to unlock the door.

ESP32-CAM Face Recognition Door Lock System (2023) (11)

So this is how the ESP32-CAM can be used to build a face recognition based security system. Complete Code can be downloaded from this link and is also given below along with a demonstration video.


#include "esp_camera.h"#include <WiFi.h>//// WARNING!!! Make sure that you have either selected ESP32 Wrover Module,// or another board which has PSRAM enabled//// Select camera model//#define CAMERA_MODEL_WROVER_KIT//#define CAMERA_MODEL_ESP_EYE//#define CAMERA_MODEL_M5STACK_PSRAM//#define CAMERA_MODEL_M5STACK_WIDE#define CAMERA_MODEL_AI_THINKER#include "camera_pins.h"const char* ssid = "Galaxy-M20";const char* password = "ac312124";#define LED_BUILTIN 4#define relay 4 #define buzzer 2boolean matchFace = false;boolean activeRelay = false;long prevMillis = 0;int interval = 5000;void startCameraServer();void setup() { Serial.begin(115200); Serial.setDebugOutput(true); Serial.println(); pinMode(relay, OUTPUT); pinMode(buzzer, OUTPUT); pinMode (LED_BUILTIN, OUTPUT); digitalWrite(LED_BUILTIN, LOW); digitalWrite(relay, LOW); digitalWrite(buzzer, LOW); camera_config_t config; config.ledc_channel = LEDC_CHANNEL_0; config.ledc_timer = LEDC_TIMER_0; config.pin_d0 = Y2_GPIO_NUM; config.pin_d1 = Y3_GPIO_NUM; config.pin_d2 = Y4_GPIO_NUM; config.pin_d3 = Y5_GPIO_NUM; config.pin_d4 = Y6_GPIO_NUM; config.pin_d5 = Y7_GPIO_NUM; config.pin_d6 = Y8_GPIO_NUM; config.pin_d7 = Y9_GPIO_NUM; config.pin_xclk = XCLK_GPIO_NUM; config.pin_pclk = PCLK_GPIO_NUM; config.pin_vsync = VSYNC_GPIO_NUM; config.pin_href = HREF_GPIO_NUM; config.pin_sscb_sda = SIOD_GPIO_NUM; config.pin_sscb_scl = SIOC_GPIO_NUM; config.pin_pwdn = PWDN_GPIO_NUM; config.pin_reset = RESET_GPIO_NUM; config.xclk_freq_hz = 20000000; config.pixel_format = PIXFORMAT_JPEG; //init with high specs to pre-allocate larger buffers if(psramFound()){ config.frame_size = FRAMESIZE_UXGA; config.jpeg_quality = 10; config.fb_count = 2; } else { config.frame_size = FRAMESIZE_SVGA; config.jpeg_quality = 12; config.fb_count = 1; }#if defined(CAMERA_MODEL_ESP_EYE) pinMode(13, INPUT_PULLUP); pinMode(14, INPUT_PULLUP);#endif // camera init esp_err_t err = esp_camera_init(&config); if (err != ESP_OK) { Serial.printf("Camera init failed with error 0x%x", err); return; } sensor_t * s = esp_camera_sensor_get(); //initial sensors are flipped vertically and colors are a bit saturated if (s->id.PID == OV3660_PID) { s->set_vflip(s, 1);//flip it back s->set_brightness(s, 1);//up the blightness just a bit s->set_saturation(s, -2);//lower the saturation } //drop down frame size for higher initial frame rate s->set_framesize(s, FRAMESIZE_QVGA);#if defined(CAMERA_MODEL_M5STACK_WIDE) s->set_vflip(s, 1); s->set_hmirror(s, 1);#endif WiFi.begin(ssid, password); while (WiFi.status() != WL_CONNECTED) { delay(500); Serial.print("."); } Serial.println(""); Serial.println("WiFi connected"); startCameraServer(); Serial.print("Camera Ready! Use 'http://"); Serial.print(WiFi.localIP()); Serial.println("' to connect");}void loop() { if (matchFace == true && activeRelay == false){ activeRelay = true; digitalWrite (relay, HIGH); digitalWrite (buzzer, HIGH); delay(800); digitalWrite (buzzer, LOW); prevMillis = millis(); } if(activeRelay == true && millis()- prevMillis > interval){ activeRelay = false; matchFace = false; digitalWrite(relay, LOW); } }

(Video) ESP32 Cam Face Recognition Door Lock System, ESP32 Face Recognition, ESP32 Camera Project

(Video) ESP32 CAM Smart IoT Bell and Door Lock Project, ESP32 Cam Project, ESP32 Cam and Blynk, IoT Camera


How do I enroll my face in ESP32 CAM? ›

To start the video streaming, click on the 'Start Stream' button at the bottom of the page. To recognize the faces with ESP32-CAM, first, we have to enroll the faces. For that, turn on the Face recognition and detection features from settings and then click on the Enroll Face button.

Tell Me More ›

What can I do with ESP32 CAM? ›

The ESP32-CAM board is an affordable development board that combines an ESP32-S chip, an OV2640 camera, several GPIOs to connect peripherals and a microSD card slot. It allows you to set up a video streaming web server, build a surveillance camera, take photos, face recognition and detection, and much more.

Read More ›

What is face recognition door lock system? ›

As soon as the person enters near the door, pi camera captures the image and face detection process is done then if it matches with database images then the door is unlocked otherwise a message with the picture of a person will be sent to the registered mobile through GSM and LAN network.

View More ›

How do you take a picture with ESP32 CAM? ›

Open your browser and type the ESP32-CAM IP Address. Then, click the “CAPTURE PHOTO” to take a new photo and wait a few seconds for the photo to be saved in SPIFFS. Then, if you press the “REFRESH PAGE” button, the page will update with the latest saved photo.

See Details ›

How do I know if my ESP32 cam is working? ›

If your ESP32-CAM AI-Thinker has no Wi-Fi connection or poor connection, it might have the external antenna enabled. If you connect an external antenna to the connector, it should work fine. Check if the jumper 0K resistor by the antenna connector is in the proper position for the desired antenna.

Show Me More ›

Does ESP32 Cam have WiFi? ›

The ESP32-CAM is based upon the ESP32-S module, so it shares the same specifications. It has the following features: 802.11b/g/n Wi-Fi.

Learn More ›


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(Video) esp32 cam face detection door lock system #esp32cam #arduinoprojects

3. ESP32-CAM Face Recognition Door Lock System (Telegram bot)

4. ESP32 CAM Beginner Guide | Face recognition | Bonus code

5. Smart WiFi Door Lock with camera using ESP32-CAM & Telegram App | Iot Projects

6. ESP32-CAM Based Face Recognition Door Lock System

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How do I use ESP32-CAM face recognition? ›

To start the video streaming, click on the 'Start Stream' button at the bottom of the page. To recognize the faces with ESP32-CAM, first, we have to enroll the faces. For that, turn on the Face recognition and detection features from settings and then click on the Enroll Face button.

Which algorithm is used in face recognition in ESP32-CAM? ›

Viola-Jones algorithm is an object detection technique focusing on the faces in an image or video. It is operative only on frontal faces. The tracking of the face is done with the help of an ESP32-CAM microcontroller.

How does face recognition door lock system work? ›

In the face recognition approach, a given face is compared with the faces stored in the database in order to identify the person. The aim is to search out a face in the database, which has the most similarity with the given face.

What are the advantages of face recognition door lock system? ›

Benefits of Face Recognition Access Control Systems

Face recognition verifies who you are, not what you carry (key card) or what you know (PIN). Hence, it's inherently more secure for controlling access to buildings. Hands free – You can simply walk up and look at the reader and the door unlocks!

How do I access my ESP32 camera from anywhere? ›

To connect to the access point on your computer, go to the Network and Internet Settings, select the “ESP32-Access-Point“ and insert the password. And it's done! Now, to access the ESP32-CAM web server page, you just need to type the IP address 192.168. 4.1 in your browser.

Which algorithm is most accurate for face recognition? ›

The most common type of machine learning algorithm used for facial recognition is a deep learning Convolutional Neural Network (CNN). CNNs are a type of artificial neural network that are well-suited for image classification tasks.

Which algorithm is best for face recognition? ›

The most popular and well-known machine learning algorithm for face recognition is the Viola-Jones algorithm. It detects photos in several stages: feature definition, feature assessment, feature classifier definition, and classifier cascade check.

Which programming language is best for face detection? ›

C++ is considered to be the fastest programming language, which is highly important for faster execution of heavy AI algorithms. A popular machine learning library TensorFlow is written in low-level C/C++ and is used for real-time image recognition systems.

What are the disadvantages of face recognition? ›

Cons of Facial Recognition
  • Threatens privacy.
  • Imposes on personal freedom.
  • Violates personal rights.
  • Data vulnerabilities.
  • Misuse causing fraud and other crimes.
  • Technology is still new.
  • Errors can implicate innocent people.
  • Technology can be manipulated.

What is the difference between face detection and face recognition? ›

While face detection trains a computer to pick out a human face, face recognition software will analyze the image. It will turn the image into a set of data about your facial features. This can include the distance between your eyes, forehead, and chin, and other geometric measurements.

What is the cost of face recognition door lock system? ›

Face Recognition Attendance Recording System With Access Control Door Lock at Rs 14797 | Face Recognition Time Attendance System in Faridabad | ID: 24005141712.

What are the advantages and disadvantages of facial recognition system? ›

Pros and Cons Table Summary
Advantages of Face DetectionDisadvantages of Face Detection
— Better security — Easy to integrate — Automated identification— Huge storage requirements — Vulnerable detection — Potential privacy issues

What are the disadvantages of smart door lock? ›

Cons Of Having A Smart Lock

Smart locks communicate with your phone, usually via Bluetooth or Wi-Fi. If your phone is stolen, you lose it or it dies, you could get locked out if you don't have a backup plan (like logging in to your account on another device).

How do you unlock doors with face ID? ›

Express Mode: Unlock the door just by holding your iPhone or Apple Watch near the lock. Require Face ID or Passcode: Hold your device near the lock, then use Face ID or Touch ID to unlock it.

Can ESP32-CAM detect motion? ›

The ESP32-CAM is in deep sleep mode with external wake up enabled. When motion is detected, the PIR motion sensor sends a signal to wake up the ESP32. The ESP32-CAM takes a photo and saves it on the microSD card. It goes back to deep sleep mode until a new signal from the PIR motion sensor is received.

Can ESP32 access internet? ›

If the router is connected to the Internet, then the ESP32 can access the Internet. The ESP32 can behave as a client: make requests to other devices connected to the network, or as a server: other devices connected to the network will send requests to the ESP32. In both cases, the ESP32 can access the Internet.

How do I control ESP32 over the Internet? ›

  1. Download Source Code. For this project, you'll need these files: ...
  2. Hosting Your PHP Application and MySQL Database. ...
  3. Preparing Your MySQL Database. ...
  4. Creating Your Dashboard Files. ...
  5. PHP Script – Update and Retrieve Output States. ...
  6. PHP Script for Database Functions. ...
  7. PHP Script – Control Buttons. ...
  8. Setting Up the ESP32 or ESP8266.

What is the goal of face detection? ›

The main objective of facial recognition is to identify individuals, whether individually or collectively. The number of false positives can vary, depending on the technology used for facial recognition. The best face identification algorithm has an error rate of 0.08%.

What is the input image for face recognition? ›

Input image guidelines

For face recognition, you should use an image with dimensions of at least 480x360 pixels. For ML Kit to accurately detect faces, input images must contain faces that are represented by sufficient pixel data. In general, each face you want to detect in an image should be at least 100x100 pixels.

How many algorithms are there in face recognition? ›

There are different types of algorithms which can be used for Face Recognition that are PCA (Principal Component Analysis), LDA (Linear Discriminant Analysis), ICA (Independent Component Analysis), EBGM (Elastic Bunch Graph Matching), Fisherfaces.

What is the accuracy of Face_recognition? ›

The model has an accuracy of 99.38% on the Labeled Faces in the Wild benchmark. This also provides a simple face_recognition command line tool that lets you do face recognition on a folder of images from the command line!

What is the accuracy score of face recognition? ›

In ideal conditions, facial recognition systems can have near-perfect accuracy. Verification algorithms used to match subjects to clear reference images (like a passport photo or mugshot) can achieve accuracy scores as high as 99.97% on standard assessments like NIST's Facial Recognition Vendor Test (FRVT).

What is the fastest face recognition? ›

Speed: FaceStation 2 can match upto 3000 matches per second (ultra-Fast performance), which makes this device as the world's fastest face recognition technology in its class.

Can Python be used for facial recognition? ›

With Python, some data, and a few helper packages, you can create your very own. In this project, you'll use face detection and face recognition to identify faces in a given image. In this tutorial, you'll build your own face recognition tool using: Face detection to find faces in an image.

Why is Python best for face recognition? ›

Faces are made of thousands of fine lines and features that must be matched. The face recognition using Python, break the task of identifying the face into thousands of smaller, bite-sized tasks, each of which is easy to face Recognition Python is the latest trend in Machine Learning techniques.

Which Python module is used for face recognition? ›

OpenCV is a popular computer vision library available in Python. It was originally written in C/C++ and now provides Python bindings. It has machine learning-backed methods for advanced face detection. The algorithms detect faces in an image by breaking it down into thousands of patterns and features that it matches.

What are 5 problems associated with facial recognition technology? ›

The top six ethical concerns related to facial recognition systems include racial bias and misinformation, racial discrimination in law enforcement, privacy, lack of informed consent and transparency, mass surveillance, data breaches, and inefficient legal support.

Do police use facial recognition software? ›

Facial recognition technology has allowed police departments across the U.S. to compare the faces of criminal suspects against other existing photos, but the tech has also proven controversial.

Why is face recognition difficult? ›

Causes of prosopagnosia (face blindness)

It can happen: if you do not develop the ability to recognise faces – this is the most common type and may run in families. from brain damage, such as following a stroke, head injury, inflammation of the brain (encephalitis), or Alzheimer's disease.

Is face recognition better than password? ›

Passwords and biometrics are used to verify your identity. Biometrics are strong to begin with, and passwords may not be. But passwords will work even if you have lotion on your hands or acquire a new scar. Biometrics allow you to get into a device or app more quickly than passwords.

Does Face ID use camera or sensor? ›

Face ID uses the TrueDepth camera and machine learning for a secure authentication solution. Face ID data – including mathematical representations of your face – is encrypted and protected with a key available only to the Secure Enclave.

Is face recognition more secure than fingerprint? ›

Fingerprint recognition can confirm individual identity more accurately than facial recognition systems. However, this may change as facial recognition systems become increasingly integrated with iris recognition, another biometric authentication method with high accuracy.

How much does it cost to install a smart lock on a front door? ›

Homeowners can expect to pay around $330 to have a smart door lock installed, although the price ranges from $200 to $460 on average. The national average cost to install a smart door lock is $330, with most homeowners paying somewhere between $200 and $460.

What is the best face recognition doorbell? ›

Best video doorbell with facial recognition

Google's Nest Doorbell with battery launched in 2021 with a solid set of features and a reasonable $180 price tag. Without any monthly fee, you get person, vehicle and package alerts, and a few hours of rolling storage.

How much does it cost to put automatic lock system? ›

The locks, the installation labor costs, and even the type of car can all change the price. But, in general, you can expect to pay anywhere from $300-$600 for labor alone. And while you can find cheap and generally ineffective automatic car door locks for as little as $100.

How do I capture an image with ESP32? ›

Demonstration. Open your browser and type the ESP32-CAM IP Address. Then, click the “CAPTURE PHOTO” to take a new photo and wait a few seconds for the photo to be saved in SPIFFS. Then, if you press the “REFRESH PAGE” button, the page will update with the latest saved photo.

How to use PIR sensor in ESP32 CAM? ›

The ESP32-CAM is in deep sleep mode with external wake up enabled. When motion is detected, the PIR motion sensor sends a signal to wake up the ESP32. The ESP32-CAM takes a photo and saves it on the microSD card. It goes back to deep sleep mode until a new signal from the PIR motion sensor is received.

What camera do I need for Windows Hello face recognition? ›

What do I need to use a Windows Hello webcam? The webcam, a USB cable to connect it to your PC, and a desktop or laptop with Windows 10 or Windows 11 are all you need.

How do I connect my ESP32 camera to my computer? ›

Selecting the Board and Port

Now connect the ESP32-CAM to your computer using a USB cable. Then, navigate to Tools > Port and choose the COM port to which the ESP32-CAM is connected. That's it; the Arduino IDE is now set up for the ESP32-CAM!

How much memory does the ESP32 CAM have? ›

The ESP32 chip contains 520KB of RAM. While it's sufficient for most projects, others may need more memory. To increase the capacity of the microcontroller, the manufacturer can add a memory chip to the board. This external RAM chip is connected to the ESP32 via the SPI bus.

Can ESP32 CAM record video? ›

Story. The SpyCam project uses the “AI Thinker ESP32-CAM” module which has a 2MP Camera, 10 I/O pins, an on-chip LED and one MicroSD slot to store the images and videos. With its tiny sized camera and 240MHz CPU is able to provide images and videos in a fair quality.

Can ESP32 do image processing? ›

Overview: ESP32 CAM Based Object Detection & Identification

This tutorial introduces the topic of ESP32 CAM Based Object Detection & Identification with OpenCV. OpenCV is an open-sourced image processing library that is very widely used not just in industry but also in the field of research and development.

How do I send ESP32 CAM captured image to Google Drive? ›

The ESP32 Cam captures the images and then sends them to Google drive. The images can be captured in two different ways. We can make it fully automatic by using a delay. So, the ESP32 Cam will capture the image after a fixed delay and then send it to Google drive.

How do you trick a PIR motion sensor? ›

One of the quick tricks you can try is to quickly turn the motion sensor ON, OFF, ON to override the motion detection and make the light stay on. To go back to motion detection mode, turn the motion sensor off, wait for about 10 seconds, and then turn it on again.

What are the 3 settings on a PIR sensor? ›

There are 3 settings on a motion sensor light: sensitivity, timer, and lux. These 3 settings determine how sensitive the light is to movement, how long the light will stay on after detecting movement, and what level of darkness the light will turn on in.

How does ESP32-CAM module work? ›

DESCRIPTION. The ESP32-CAM is a small size, low power consumption camera module based on ESP32. It comes with an OV2640 camera and provides onboard TF card slot. The ESP32-CAM can be widely used in intelligent IoT applications such as wireless video monitoring, WiFi image upload, QR identification, and so on.

Is Windows Hello the same as face ID? ›

Windows Hello is a more personal, more secure way to get instant access to your Windows 11 devices using a PIN, facial recognition, or fingerprint. You'll need to set up a PIN as part of setting up fingerprint or facial recognition sign-in, but you can also sign in with just your PIN.

Does Windows Hello face unlock work with normal camera? ›

Using your Windows 10 or Windows 11 laptop's built-in webcam, Hello uses facial recognition to get you in and working in under two seconds. Unfortunately, not every webcam works with Windows Hello.


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