This month SensiML is pleased to announce the SensiML Analytics Toolkit now provides native support for building intelligent TinyML edge sensor algorithms on the Arduino Nano 33 BLE Sense board.

A popular platform amongst makers, application innovators, and the TensorFlow Lite AI community, our support of the Arduino Nano 33 BLE Sense allows sensor algorithms to be built and executed autonomously on the device using either classic machine learning classifiers or Google TensorFlow Lite for Microcontrollers.

Based on the Nordic nRF52840, the Nano 33 BLE Sense has an array of sensors including microphone, IMU (accel/gyro/mag), ambient light, pressure, temperature, and humidity sensing. As such, it’s a capable and compact device for building SensiML edge AI algorithms for a variety of applications.

For building the firmware, we chose to use PlatformIO as it allows the user easy means for changing and adding build flags, as well as allowing for multiple build environments.

Our implementation also utilizes our latest raw sensor data collection interface we call the Simple Streaming Interface, allowing for easy to configure custom sensor capture.

Learn more about how to use SensiML Analytics Toolkit with Nano33 BLE Sense and PlatformIO IDE here.

To learn more about the Arduino Nano 33 BLE Sense visit the Arduino product page.

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Arduino Nano 33 BLE Sense


Supports simplified CSV Streaming mode output for easy to configure custom sensor capture.