FireBeetle 2 ESP32-S3 with Camera and External Antenna

The ESP32-S3-WROOM-1-N16R8 comes with 16MB Flash and 8MB PSRAM for storing more data. The acceleration for neural network computing and signal processing workloads provided by the ESP32-S3 chip make the module an ideal choice for a wide variety of applications, such as speech recognition, image recognition and more.

Powerful Chips and Expanded Storage

The acceleration for neural network computing and signal processing workloads provided by the ESP32-S3 chip makes the module an ideal choice for a wide variety of applications, such as speech recognition and image recognition.

For instance, when training for facial recognition, it is possible to store a greater number of facial models. This allows for faster results when conducting data comparisons.

WiFi and Bluetooth

In addition, the FireBeetle 2 ESP32-S3 supports WiFi and Bluetooth 5 (LE) dual-mode communication that reduces the difficulty of networking, with both Bluetooth Mesh protocol and Espressif WiFi Mesh supported for more stable communication and a larger coverage area. With the support of Matter protocol, the board can be used to develop industrial standard smart home devices for a wider range of IoT scenarios.

Onboard Camera Interface

The board has an onboard camera interface for easy connection with a compatible camera. The board also uses an independent camera power supply circuit to help reduce interference from other signals to the camera. The board comes with an OV2640 camera that offers 2 megapixel, 68° FOV and up to 1600×1200 resolution.

Image Recognition

The FireBeetle 2 ESP32-S3 offers an onboard camera interface for easy connection with a camera (included). Also, an independent camera power supply circuit is designed, which helps reduce interference from other signals to the camera. The board comes with an OV2640 camera that offers 2 megapixels, a 68°FOV, and up to 1600*1200 resolution.

For instance, in a smart home scenario, the board's camera can be utilised to monitor the situation at home. When someone enters, it can automatically send notifications and store the captured image data for reporting purposes.

Power Options

The controller integrates a power management function which enables users to charge a LiPo battery and turn the hardware on/off.

Programming Flexibility

Programming can be achieved via the Arduino IDE, ESP-IDF and MicroPython. Both C and Python are supported!

GDI Display Ready

There is also an onboard GDI port for use with DFRobot GDI-compatible displays.

Features

ESP32-S3 module with AI Acceleration

16MB Flash & 8MB PSRAM, more storage space

Onboard camera interface & independent camera power supply, easy to connect and strong anti-interference

Power management integrated, support Li-ion battery charging and hardware On/OFF controlling

Onboard GDI for easy connection with screens

Wi-Fi and Bluetooth 5 dual-mode communication

Specifications

Basic Parameters

Operating Voltage: 3.3V

Type-C Input Voltage: 5V DC

VCC Input Voltage: 5V DC

Max Charging Current: 1A

Operating Temperature: -20 to 70℃

Dimension: 25.4x60mm/1x2.36”

Hardware

Processor: Xtensa® dual-core 32-bit LX7 microprocessor

Main Frequency: 240 MHz

SRAM: 512KB

ROM: 384KB

Flash: 16MB

PSRAM: 8MB

RTC SRAM: 16KB

USB: USB 2.0 OTG full-speed

WiFi

WIFI Protocol: IEEE 802.11b/g/n

Bandwidth: Support 20 MHz and 40 MHz at 2.4 GHz band

WIFI Mode: Station, SoftAP, SoftAP+Station combined mode

WIFI Frequency: 2.4GHz

Frame Aggregation: TX/RX A-MPDU, TX/RX A-MSDU

Bluetooth

Bluetooth Protocol: Bluetooth 5, Bluetooth mesh

Bluetooth Frequency: 125 Kbps, 500 Kbps, 1 Mbps, 2 Mbps

Ports

Digital I/O x26

LED PWM Controller 8 Channels

SPI x4

UART x3

I2C x2

I2S x2

IR Transceiver: transmit channel x5, receive channel x5

2×12-bit SAR ADC, 20 Channels

DMA Controller: transmit channel x5, receive channel x5