Seeed Studio XIAO ESP32S3 Sense – 2.4GHz WiFi, BLE 5.0, OV2640 camera, microphone, 8MB PSRAM, 8MB FLASH, battery charge supported
36.00 лв. с вкл. ДДС
В наличност
Seeed Studio XIAO ESP32S3 Sense е компактна развойна платка с камера и микрофон, работеща с микроконтролер ESP32-S3R8 (Xtensa LX7 dual-core, 32-bit processor running up to 240 MHz) – datasheet.
Комплектът съдържа:
- Платка Seeed Studio XIAO ESP32S3 Sense – 1 бр.
- Надграждаща платка с камера – 1 бр.
- Антена – 1 бр.
Важно: В комплекта няма USB кабел! USB кабел за връзка с компютър – USB-A USB-C
Характеристики:
- Микроконтролер: ESP32-S3R8
- Xtensa LX7 dual-core, 32-bit processor running up to 240 MHz
- FLASH: 8MB
- PSRAM: 8MB
- 2,4 GHz Wi-Fi (802.11 B/G/N)
- Bluetooth 5 (LE) и Bluetooth Mesh
- Надграждаща платка:
- OV2640 камера (1600*1200 resolution)
- цифров микрофон
- конектор за microSD карта
- Захранване: USB 5V или от Li-Po батерия 3,7V
- Зарядно за Li-Po батерия 3,7V, осигуряващо до 100mA (Важно: изводите за Li-Po батерия се намират от долната страна на платката! Няма предвиден конектор за батерия, а само изводи където да се запоят проводниците на батерията!)
- Работно напрежение I/O портове: 3,3V
- Входно изходни портове (PINOUT): 11 броя (1x UART, 1x I2C, 1x I2S, 1x SPI, 11x GPIO(PWM), 9x ADC, 1x User LED, 1x Charge LED)
- Поддържа USB native, UART, I2C, SPI, I2S и др.
- Има USB-C конектор, 2 светодиодa (1 user LED, 1 charge LED) и два бутона (1x reset, 1x boot)
- Програмира се през USB с Arduino IDE, със CircuitPython и др.
- Размери платка: 21mm x 17,5mm
- WiFi/BT антена: външна, PCB, uFL конектор
- Микроконтролер: ESP32-S3R8
Допълнителна информация:
- Seeed Studio XIAO ESP32S3 Sense. Подробно описание
- Seeed Studio XIAO ESP32S3 Wiki. Ръководство
- Pinout
- ESP32-S3R8 datasheet
PRODUCT DETAILS EN:
Seeed Studio XIAO Series are diminutive development boards, sharing a similar hardware structure, where the size is literally thumb-sized. The code name „XIAO“ here represents its half feature „Tiny“, and the other half will be „Puissant“.
Seeed Studio XIAO ESP32S3 Sense integrates a camera sensor, digital microphone, and SD card support. Combining embedded ML computing power and photography capability, this development board can be your great tool to get started with intelligent voice and vision AI.
Feature
- Powerful MCU Board: Incorporate the ESP32S3 32-bit, dual-core, Xtensa processor chip operating up to 240 MHz, mounted multiple development ports, Arduino / MicroPython supported
- Advanced Functionality: Detachable OV2640 camera sensor for 1600*1200 resolution, compatible with OV5640 camera sensor, integrating additional digital microphone
- Great Memory for more Possibilities: Offer 8MB PSRAM and 8MB FLASH, supporting SD card slot for external 32GB FAT memory
- Outstanding RF performance: Support 2.4GHz Wi-Fi and BLE dual wireless communication, support 100m+ remote communication when connected with U.FL antenna
- Thumb-sized Compact Design: 21 x 17.5mm, adopting the classic form factor of XIAO, suitable for space-limited projects like wearable devices
- Pretrained Al model from SenseCraft Al for no-code deployment
Description
Seeed Studio XIAO ESP32S3 Sense is built around a highly-integrated, Xtensa processor ESP32-S3R8 SoC, which supports 2.4GHz WiFi and low-power Bluetooth® BLE 5.0 dual-mode for multiple wireless applications. It has lithium battery charge management capability.
As the advanced version of Seeed Studio XIAO ESP32S3, this board comes with a plug-in OV2640 camera sensor for displaying full 1600*1200 resolution. The base of it is even compatible with OV5640 for supporting up to 2592*1944 resolution. The digital microphone is also carried with the board for voice sensing and audio recognition. SenseCraft AI provides various pre-trained Artificial Intelligence (AI) models and no-code deployment to XIAO ESP32S3 Sense.
With powerful SoC and built-in sensors, this development board has 8MB PSRAM and 8MB FLASH on the chip, an additional SD card slot for supporting up to 32GB FAT memory. These allow the board for more programming space and bring even more possibilities into embedded ML scenarios.