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INTRODUCTION
FireBeetle 2 ESP32-S3-U is a high-performance main controller built around the ESP32-S3-WROOM-1U-N16R8 module. ESP32-S3-WROOM-1U-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, recognition, and so on.
FireBeetle 2 ESP32-S3-U offers an onboard camera interface for easy connection with a camera. 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, 68° FOV, and up to 1600*1200 resolution. Besides, its onboard easy-to-connect GDI greatly saves the trouble of wiring for using with a screen. Meanwhile, the controller integrates a power management function, which allows users to charge a Li-ion battery and turn the hardware on/off.
In addition, FireBeetle 2 ESP32-S3-U supports WiFi and 5 (LE) dual-mode communication, which reduces the difficulty of networking. Meanwhile, both Mesh protocol and Espressif WiFi Mesh are supported for more stable communication and a larger coverage area. With the support of Matter protocol, the microcontroller can be used to develop industrial standard home devices for a wider range of IoT and AIoT (Artificial Intelligence of Things) scenarios.
FireBeetle 2 ESP32-S3-U can be programmed by IDE, ESP-IDF, and MicroPython. Both C and Python are supported.
recognition
Video picture transmission
Comparison Table
FireBeetle 2 Board ESP32-S3 (N16R8) AIoT Microcontroller | FireBeetle 2 Board ESP32-S3-U (N16R8) AIoT Microcontroller | |
WiFi | Soldered on the board | Routed through a cable |
| Soldered on the board | Routed through a cable |
Features | Cohesive design, more visually appealing | Better signal quality |
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 5 dual-mode communication
APPLICATIONS
AIoT-related projects
Speech recognition
recognition
SPECIFICATION
Basic Parameters
Operating Voltage: 3.3V
Type-C Input Voltage: 5V
VCC Input Voltage: 5V
Charging Current: 1A
Operating Temperature: -20 to 70
Dimension: 25.4x60mm/1x2.36"
Hardware Information
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
Protocol: 5, mesh
Frequency: 125 Kbps, 500 Kbps, 1 Mbps, 2 Mbps
Ports
Digital I/O x26
LED PWM Controller 8 Channels
SPI x4
UART x3
I2C
I2S
IR Transceiver: transmit channel x5, receive channel x5
2×12-bit SAR ADC, 20 Channels
DMA Controller: transmit channel x5, receive channel x5
PROJECTS
Project: DIY a plant growth recorder with ESP32 S3
Introduction: I plan to create a DIY plant growth recorder that will allow me to monitor the entire growth process of my plants from seedling to maturity, while tracking environmental conditions throughout.
Figure: DIY a plant growth recorder with ESP32 S3
DOCUMENTS
Product wiki
ESP32-S3-WROOM-1 Datasheet
ESP32-S3 Chip Datasheet
Schematics
Dimension
SHIPPING LIST
FireBeetle 2 Board ESP32-S3-U (N16R8) x1
OV2640 Camera x1
2.4GHz WIFI&BLE Antenna x1
18pin-2.54mm Pin Header x1
18pin-2.54mm Female Header x1
14pin-2.54mm Pin Header x1
14pin-2.54mm Female Header x1
