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Seeed Studio XIAO ESP32C3

RWF 20,000

The Seeed Studio XIAO ESP32-C3 is a small, compact development board powered by the ESP32-C3 chip, which is part of the ESP32 family of microcontrollers from Espressif. This board is ideal for low-power IoT applications and provides Wi-Fi and Bluetooth LE (Low Energy) connectivity in a very compact form factor.


Product Description

Seeed Studio XIAO ESP32C3 has equipped a highly integrated ESP32-C3 chip, built around a 32-bit RISC-V chip processor with a four-stage pipeline that operates at up to 160 MHz. The board equips highly integrated ESP32-C3 SoC. The chip has been installed with a complete 2.4 GHz Wi-Fi subsystem which means it supports Station mode, SoftAP mode, SoftAP & Station mode, and promiscuous mode for multiple Wi-Fi applications. It works under an ultra-low power state, also supporting features of Bluetooth 5 and Bluetooth mesh. There are 400 KB SRAM & 4 MB Flash on the chip, allowing for more programming space, and bringing more possibilities to the IoT control scenarios.

Features

  • Processor: esp32-C3 SoC
  • Wireless: Complete 2.4 GHZ Wi-Fi subsystem and Bluetooth 5.0/Bluetooth Mesh
  • On-chip memory: 400 KB SRAM & 4 MB Flash
  • Power: -Circuit operating voltage:3.3V
-Charging current:50 mA/100 mA -Input voltage (VIN):5V
  • Outstanding RF performance: Powerful ESP32-C3 SoC and U. FL antenna provided that supports Wi-Fi/Bluetooth connection over 100 m.
  • Deep sleep power consumption: Deep sleep model:>44?A
  • Wi-Fi Enabled power consumption: -Active model:<75 mA.
-Modem-sleep model:<25 mA -Light-sleep model:<4 mA
  • Thumb-size Design:21 x 17.5 mm overall dimension, portable and lightweight.
  • Low power consumption: Lowest as 44 ?A (deep sleep mode), with 4 working modes available.
  • Onboard battery charge IC:Supports battery charging, great for various wearable scenarios and wireless IoT applications.
BLE Enabled Power Consumption: -Modem-sleep model:<27 mA. -Light sleep model:<10 mA

Applications

  • Internet of Things
  • Wearable devices
  • Health monitoring
  • Education
  • Low-Power (LP) networking
  • Rapid prototyping

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