Arduino Nano 33 Ble Sense with Header-Rev 2

SKU: VM01155

Price:
Sale price Rs. 3,305.08
(excl.18% GST)
Rs. 3,900.00

Description

Arduino Nano 33 Ble Sense with Header-Rev 2

The Arduino Nano BLE Sense (Rev-2) is a compact, powerful development board designed for embedded AI, IoT, and sensor-rich applications. It is built around a 32-bit ARM Cortex-M4F microcontroller with Bluetooth Low Energy, and it integrates multiple onboard sensors for motion, environment, sound, color, and proximity sensing. Rev-2 improves sensor accuracy and reliability compared to earlier versions while maintaining the classic Nano form factor for easy breadboard and prototype use.

Technical Specifications:

  • Microcontroller: Nordic nRF52840 (ARM Cortex-M4F, 64 MHz, FPU)
  • Operating Voltage: 3.3 V
  • Input Voltage: 5 V via USB
  • Flash Memory: 1 MB
  • SRAM: 256 KB
  • Wireless: Bluetooth Low Energy 5.0
  • USB Interface: Micro-USB
  • GPIO Pins: 14 digital I/O, 8 analog inputs
  • PWM: Supported on multiple digital pins
  • I2C / SPI / UART: Supported
  • Onboard Sensors:
    • 9-axis IMU (accelerometer, gyroscope, magnetometer)
    • Temperature and humidity sensor
    • Barometric pressure sensor
    • Digital microphone
    • Color and gesture sensor
    • Proximity and ambient light sensor
  • Dimensions: Nano form factor (approx. 45 × 18 mm)

Features:

  • Integrated multi-sensor platform for rapid prototyping
  • Bluetooth Low Energy 5.0 for low-power wireless communication
  • Supports Arduino IDE, Arduino Cloud, and TinyML workflows
  • Improved sensor selection and layout in Rev-2 for better accuracy
  • Compact size suitable for wearables and embedded systems
  • Low power consumption with multiple sleep modes
  • Native USB support for easy programming and debugging

Applications:

  • Edge AI and TinyML projects
  • Wearable devices and motion tracking
  • Environmental monitoring systems
  • IoT sensor nodes with BLE connectivity
  • Smart home and automation projects
  • Gesture- and voice-controlled interfaces
  • Educational projects in embedded systems and machine learning

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