ESP32-CAM WiFi + bluetooth Camera Module Development Board ESP32 With Camera Module OV2640

ESP32-CAM WiFi + bluetooth Camera Module Development Board ESP32 With Camera Module OV2640
Product Code: ESP32CAOV2640
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Price: R180.00
Ex Tax: R180.00
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ESP32-CAM WiFi + bluetooth Camera Module Development Board ESP32 With Camera Module OV2640.

Description:
 
1. ESP32-CAM is a WIFI+ bluetooth dual-mode development board that uses PCB on-board antennas and cores based on ESP32 chips. It can work independently as a minimum system.
2. ESP integrates WiFi, traditional bluetooth and BLE Beacon, with 2 high-performance 32-bit LX6 CPUs, 7-stage pipeline architecture, main frequency adjustment range 80MHz to 240MHz, on-chip sensor, Hall sensor, temperature sensor, etc.
3. Fully compliant with WiFi 802.11b/g/n/e/i and bluetooth 4.2 standards, it can be used as a master mode to build an independent network controller, or as a slave to other host MCUs to add networking capabilities to existing devices.
4. ESP32-CAM can be widely used in various IoT applications. It is suitable for home smart devices, industrial wireless control, wireless monitoring, QR wireless identification, wireless positioning system signals and other IoT applications. It is an ideal solution for IoT applications.

Features:
Ultra-small 802.11b/g/n Wi-Fi + BT/BLE SoC module

  • Low-power dual-core 32-bit CPU for application processors
  • Up to 240MHz, up to 600 DMIPS
  • Built-in 520 KB SRAM, external 4M PSRAM
  • Supports interfaces such as UART/SPI/I2C/PWM/ADC/DAC
  • Support OV2640 and OV7670 cameras with built-in flash
  • Support for images WiFI upload
  • Support TF card
  • Support multiple sleep modes
  • Embedded Lwip and FreeRTOS
  • Support STA/AP/STA+AP working mode
  • Support Smart Config/AirKiss One-click distribution network
  • Support for serial local upgrade and remote firmware upgrade (FOTA)
  • Support secondary development.

Resources

 
Note:
 
This product contains the OV2640 Camera Module. If you need to use the OV7670 camera, please purchase it separately.
 
Package Included:
 
1 x ESP32-CAM Module
1 x Camera Module OV2640 2MP

Pin definition details

Programming connection Diagram

Resources

Seting up your board for the first time

Let’s take a look at what it takes to get the board up and running. There are a few ways of programming the ESP32-CAM, but we’re most familiar with
the Arduino IDE, so we tried this.

To install the ESP32 boards, go to File > Preferences and add ‘https://dl.espressif.com/dl/package_esp32_index.json’ to the Additional Board Manager URLs box – this is a comma-separated list, so add a comma before it if you already have any URLs in the box.

In the Tools > Boards section, you should now have an ESP32 Arduino section. In that section, you should see an entry for AI Thinker ” ESP32-CAM. However, we weren’t able to program the board using this. Instead, we used the definition for another, similar board: the ESP32 Wrover Module.

Once you’ve selected this, you should find the web server example sketch, which is a great test to make sure everything’s connected properly. This is in Files > Examples > ESP32 > Camera > CameraWebServer.

You’ll need to make a few changes to this sketch. First, add ‘//’ to the start of the following line to comment it out.

#define CAMERAMODELWROVER_KIT

Then delete the // at the start of this line to enable it.

//#define CAMERAMODELAI_THINKER

Finally, you’ll need to enter your WiFi details in the following lines:

const char* ssid = “”;
const char* password = “”;

You’ll also need to set the Partition Scheme to Huge App and the Upload Speed to 115200 (these are in the Tools menu). That’s the software side of things set up for this board, so let’s now take a look at the hardware.

You may notice that there’s no USB port on this board, so you’ll need a USB to serial adapter to program it. Any USB to UART adapter should work, and they are available for a few rands. We used a Particle Debugger because we happened to have one with us, but this is overkill for this project.

You’ll need four connections between the UART adapter and the ESP32 Camera: 5 V (this may be labelled VUSB) to 5 V, GND to GND, TX on the USB adapter to U0R on the ESP32-CAM, and RX on the adapter to U0T on the ESP32-CAM. Also, you’ll need to connect IO0 on the ESP32-CAM and GND – this puts the board into flashing mode, and we’ll remove this once we’ve programmed the board.

With that setup,you can plug your USB to UART adapter into your computer’s USB port, and now you should be able to select a Port from the Tools menu in the Arduino IDE.

Press the upload button (the arrow icon) and – after a short wait – your code should be on your board. There’ll be a message in the black box at the bottom of the screen saying that the upload was successful (or not).

You can now unplug the IO0 to GND connection but leave everything else connected for now. Open the serial monitor in the Arduino IDE, set the baud rate to 115200 (bottom-right corner), and press the reset button on the ESP32-CAM.
In the serial monitor, you’ll see a bit of debug code followed by something like:

Camera Ready! Use ‘http://x.x.x.x’ to connect

If you point a web browser to that URL, you’ll see the camera control page. Press ‘Start stream’ to see the output of the camera.

For a cheap IP webcam, this works well if you’re happy using the Arduino IDE to upload credentials. You can get streaming output at up to 1284×1024 pixels (we got a frame rate of about 6 fps at this size, and faster at smaller sizes). The fact that it outputs data in a standard format, and so works well with open-source IoT hubs, is a bonus.

There’s also some rudimentary face recognition, but we found this to be quite unreliable.

The cooling on the board does struggle if you’re streaming continuously. The board gets very warm, and some users report it stopping working.

We’d expect this to be a bigger problem if the unit is enclosed, so if you plan to use a case of some sort, you may need to take this into account with a heat sink or even a fan.

 

Now if you want to do some Image recognition here is more projects to look at.

There is a library for basic image gathering available at https://github.com/espressif/esp32-camera and an image recognition framework at https://github.com/espressif/esp-who

or https://github.com/espressif/esp-face

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