Official authentic Arduino Nano 33 BLE Sense Rev2 with headers is a compact, powerful, AI-ready development board designed for embedded intelligence, TinyML, IoT, automation, robotics, and smart sensing applications. This original Arduino board is based on the Nordic nRF52840 microcontroller and operates at 3.3V, offering built-in Bluetooth Low Energy, ultra-low power performance, and a rich set of onboard sensors. Available from BDTronics website seller in Bangladesh, this board allows developers, students, researchers, and engineers to build intelligent systems without external sensors or additional modules.

Arduino Nano 33 BLE Sense Rev2 supports edge computing and on-device machine learning using TensorFlow Lite and Edge Impulse, making it ideal for gesture recognition, voice detection, motion tracking, environment monitoring, and AI-based automation projects. The board includes a microphone, IMU, temperature sensor, humidity sensor, pressure sensor, and gesture/light/proximity sensor, enabling fast prototyping for AI, IoT, and embedded system development.

This version comes with pre-soldered headers for easy breadboard use, rapid testing, and stable connections. The native USB interface allows direct programming and serial communication without extra adapters. With 1MB flash memory and 256KB SRAM, this Arduino Nano model is suitable for advanced real-time processing and data-driven applications. BDTronics provides this original Arduino Nano 33 BLE Sense Rev2 for reliable performance in professional and educational projects across Bangladesh.

Key Applications and Use Cases

• AI-based wearable device development using motion and gesture recognition

• Voice-controlled systems using onboard digital microphone

• Smart home and room monitoring solutions with temperature and humidity sensing

• Edge AI and TinyML experimentation and deployment

• IoT sensor node development with Bluetooth Low Energy

• Environmental data logging and monitoring systems

• Robotics motion detection and orientation tracking

• Prototyping machine learning models on microcontrollers

• Gesture-controlled automation systems

• Research, education, and engineering training projects

• Embedded AI development without external sensors

• Low power wireless sensor networks

• Data acquisition and signal processing projects

• Smart agriculture monitoring nodes

• Industrial sensing and automation prototypes

Edge AI and TinyML Capability

• Supports TensorFlow Lite for Microcontrollers for running AI models directly on the board

• Compatible with Edge Impulse for data collection, training, and deployment

• Enables real-time inference without cloud dependency

• Processes sensor data locally for faster response and privacy

• Suitable for motion classification, anomaly detection, and pattern recognition

• Optimized for low-power AI applications

• Allows training using real sensor data from the board

• Works with Arduino IDE and supported ML frameworks

Built-in Sensor Set

• 9-axis motion sensing using BMI270 IMU and BMM150 magnetometer

• Digital microphone MP34DT06JTR for audio and voice detection

• Gesture, proximity, light, and color sensing using APDS9960

• Barometric pressure measurement using LPS22HB

• Temperature and humidity sensing using HS3003

• Enables multi-sensor fusion applications

• Eliminates need for external sensor modules

• Suitable for AI-based sensor data classification

Connectivity and Interface

• Bluetooth Low Energy powered by nRF52840

• Native USB support for programming and serial communication

• UART interface for serial peripherals

• SPI interface for high-speed communication

• I2C interface for sensors and expansion

• Supports external interrupts on all digital pins

• PWM available on all digital pins

• Breadboard-friendly Nano form factor with headers

• Compatible with Arduino IDE and libraries

How to Use and Getting Started

• Connect the Arduino Nano 33 BLE Sense Rev2 to a computer using USB

• Install Arduino IDE and select the correct board from Boards Manager

• Install Arduino Mbed OS Nano Boards package

• Select the correct COM port

• Write or upload example sketches for sensors, BLE, or AI

• Use Edge Impulse or TensorFlow Lite to train models

• Upload trained model to the board

• Read sensor data directly without external components

• Integrate with BLE for wireless communication

• Power via USB or external input within voltage limits

• Mount easily on breadboards or project enclosures

• Use in prototypes, demos, and production testing

Power and Electrical Characteristics

• Operates at stable 3.3V logic level

• Input voltage supported up to 21V

• Efficient low-power consumption for battery projects

• 15 mA maximum per I/O pin

• Suitable for portable and wearable applications

• Supports USB-powered and external power setups

• Designed for long-term embedded operation

Development and Compatibility

• Fully compatible with Arduino IDE

• Supports C and C++ programming

• Works with TensorFlow Lite Micro

• Compatible with Edge Impulse platform

• Supports Arduino libraries and community examples

• Suitable for beginners and advanced developers

• Ideal for academic, research, and commercial prototyping

• Supported across Windows, Linux, and macOS

Features:

• Official authentic Arduino Nano 33 BLE Sense Rev2 with headers

• AI-ready microcontroller with Bluetooth Low Energy

• Onboard motion, environmental, and gesture sensors

• Edge computing and TinyML support

• Compact Nano form factor

• Pre-soldered headers for easy use

• Native USB connectivity

• Low power operation

• High-performance 64MHz ARM Cortex-M4F

• Suitable for wearable, IoT, and AI projects

• Available in Bangladesh from BDTronics

• Ideal for students, engineers, and developers

• Supports real-time data processing

• Enables smart sensing without external hardware

Specifications:

• Microcontroller: nRF52840

• Operating Voltage: 3.3V

• Input Voltage Limit: 21V

• DC Current per I/O Pin: 15 mA

• Clock Speed: 64 MHz

• Flash Memory: 1 MB

• SRAM: 256 KB

• EEPROM: None

• Digital I/O Pins: 14

• PWM Pins: All digital pins

• UART: 1

• SPI: 1

• I2C: 1

• Analog Input Pins: 8 (12-bit, 200 ksps)

• Analog Output: PWM only

• External Interrupts: All digital pins

• Built-in LED Pin: 13

• USB: Native via nRF52840

• IMU: BMI270 and BMM150

• Microphone: MP34DT06JTR

• Gesture / Light / Proximity / Color Sensor: APDS9960

• Barometric Pressure Sensor: LPS22HB

• Temperature and Humidity Sensor: HS3003

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