Arduino Nano 33 BLE Sense Rev2
Sensor-packed Nano board with nRF52840 ARM Cortex-M4F at 64MHz, BLE 5.0, 9-axis IMU, microphone, temperature, humidity, pressure, light, and gesture sensors — designed for TinyML and edge AI projects in a 45×18mm form factor.
$39.50
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Specifications
Components
Nordic nRF52840 at 64MHz with FPU, DSP, 1MB flash, 256KB RAM, and multiprotocol radio supporting BLE 5.0, Thread, and Zigbee.
Bosch BMI270 ultra-low-power 6-axis IMU with accelerometer and gyroscope for motion tracking and gesture recognition.
Bosch BMM150 3-axis geomagnetic sensor for compass heading and magnetic field detection.
STMicroelectronics MP34DT06JTR omnidirectional digital MEMS microphone with PDM output for voice and audio capture.
Renesas HS3003 high-accuracy temperature and humidity sensor with I2C interface.
STMicroelectronics LPS22HB MEMS barometric pressure sensor with 24-bit output and I2C/SPI interface.
Broadcom APDS-9960 digital proximity, ambient light, RGB color, and gesture sensor with I2C interface.
Bus Interfaces
GPIO Map
Overview
The Arduino Nano 33 BLE Sense Rev2 is a compact, sensor-rich development board built around the Nordic nRF52840 ARM Cortex-M4F running at 64MHz with 1MB flash, 256KB RAM, and Bluetooth LE 5.0. What makes it unique in the Nano family is its comprehensive onboard sensor suite — no external hardware needed to start building AI-powered projects.
Integrated sensors include a 9-axis IMU (accelerometer, gyroscope, magnetometer), digital microphone, temperature and humidity sensor, barometric pressure sensor, proximity/light/gesture sensor, and color detection. This combination makes it ideal for TinyML applications using TensorFlow Lite Micro and Edge Impulse, enabling on-device gesture recognition, voice keyword detection, anomaly detection, and environmental classification.
Operating at 3.3V logic with 14 digital I/O pins and 8 analog inputs, the board fits the standard Nano footprint for breadboard compatibility. It's the go-to board for anyone exploring machine learning on microcontrollers without the complexity of connecting multiple external sensors.
Use Cases
4Educational Platform
Development boards suitable for teaching programming, electronics, and embedded systems concepts.
Wearable
Body-worn computing devices including smartwatches, fitness bands, and health monitors.
Environmental Monitoring
Monitoring environmental conditions like temperature, humidity, air quality, and weather data using remote sensors.
IoT
Internet of Things applications including connected sensors, actuators, and smart devices that communicate over WiFi, BLE, LoRa, or other wireless protocols.
Resources
Where to Buy
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