The Arduino Nano 33 BLE Rev2, an upgraded version of the Arduino Nano 33 BLE board that was launched in 2019, is the latest development in the Internet of Things (IoT) hardware field. The significant updates of this new board include the integration of two Inertial Measurement Unit (IMU) sensors, namely the BMI270 6-axis accelerometer and gyroscope, and the BMM150 3-axis magnetometer, instead of using only one IMU sensor as in the previous version.
These updates are based on user feedback and have been incorporated to enhance the functionality and performance of the board. In addition to the dual IMU sensors, the board also features new pads and test points for Universal Serial Bus (USB), Serial Wire Debug Input/Output (SWDIO), and Serial Wire Clock (SWCLK). Furthermore, a new Voltage USB (VUSB) soldering jumper has been added, and the power circuitry has been revamped.
Unpacking the Arduino Nano 33 BLE Rev2 Specifications
The Arduino Nano 33 BLE Rev2 continues to be powered by the nRF52840 Bluetooth Low Energy (LE) module, which is part of the u-Blox NINA B306. The board retains Arduino Nano compatibility with two rows of 15-pin headers. However, the 9-axis IMU sensor has been replaced with the BMI270 and BMM150 chips.
The specifications of the new board include an Arm Cortex-M4F microcontroller operating at 64MHz. The board also includes 1MB Flash memory and 256KB RAM for storage. The BLE 5.0 LE facilitates a link rate of up to 2 Mbps, with long-range support, and has a +8 dBm TX power and -95 dBm sensitivity. The power consumption of the board is 4.8 mA in TX (0 dBm) and 4.6 mA in RX (1 Mbps).
The board also supports expansion with 2x 15-pin expansion headers that include General-Purpose Input/Output (GPIO), Serial Peripheral Interface (SPI), Inter-Integrated Circuit (I2C), Universal Synchronous/Asynchronous Receiver/Transmitter (USART), Pulse Width Modulation (PWM), Analog-to-Digital Converter (ADC), Digital-to-Analog Converter (DAC), reset, and power signals. However, it is essential to note that the board only supports 3.3V I/Os and is not 5V tolerant.
Improved Sensor Capabilities and Debugging
The Arduino Nano 33 BLE Rev2 is equipped with a BMI270 6-axis accelerometer and gyroscope, and a BMM150 3-axis magnetometer with a 0.3μT resolution. This enhanced sensor capability allows for more accurate and precise measurements. Debugging is facilitated via the micro USB port and the 6-pin solder pads. New pads and test points for USB, SWDIO, and SWCLK have been added to streamline the debugging process.
Power Supply and Dimensions
The power supply for the board can be provided through a 5V micro USB port or VUSB pin on the header. The board also supports a voltage input ranging from 5V to 18V via the Vin pin. The MP2322 DC-DC step-down converter regulates the input voltage up to 21V with a minimum of 65% efficiency at minimum load and more than 85% efficiency at 12V. The dimensions of the board are 45 x 18 mm, which is compatible with Arduino Nano, and it weighs just 5 grams.
Getting Started with Arduino Nano 33 BLE Rev2
The Arduino Nano 33 BLE Rev2 is compatible with the first generation of the board and can be programmed with Arduino or MicroPython. Users are advised to update the board support and libraries to the latest version for optimal performance. The board can be purchased for $24.17 / 22.80 Euros without headers or $26.92 / 25.40 Euros without headers on the Arduino store.
For those interested in further technical details, getting started instructions, and tutorials, these resources can be found on the official documentation website.
It is noteworthy that the Arduino Nano 33 BLE Sense Rev2 was introduced last year with the same BMI270 and BMM150 chips, plus additional sensors, including the MP34DT06JTR microphone, APDS9960 gesture, light, proximity sensor, LPS22HB barometric pressure sensor, and Renesas HS3003 temperature & humidity sensor.
The development of the Arduino Nano 33 BLE Rev2 is a testament to the continuous advancements in IoT technology. This board, with its improved sensor capabilities and updated features, is expected to play a significant role in future IoT projects and applications.
