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Rapidly Develop Machine Learning Models for Edge Applications Over BLE

Embedded Devices, TinyMLEdge Impulse has announced official support for the Nordic Thingy:53 prototyping platform!

Jenny Plunkett

June 14, 2022

Today, we are excited to announce our official support for the Nordic Thingy:53 prototyping platform! The kit is based on the nRF5340 SoC, which features a dual-core Cortex-M33 MCU and supports BLE, Thread, Zigbee, and proprietary 2.4 GHz protocols. 

The Thingy:53 is equipped with several sensors that enable you to create powerful IoT projects. You have access to a color and light sensor and environmental sensor for temperature, humidity, air quality and air pressure. Moreover, there’s also a three-axis accelerometer and inertial measurement unit (IMU). Adding in the embedded 1350mAh rechargeable Li-Po battery you’ve got the perfect platform for ingesting data and quickly deploying proof-of-concept tinyML applications.

Every Nordic Thingy:53 is shipped with Edge Impulse firmware already flashed. You'll be able to sample raw data, build models, and deploy trained machine learning models directly out-of-the-box via the Edge Impulse Studio or brand new Nordic nRF Edge Impulse iPhone and Android apps over BLE connection!

Read the How do I get started? sectionHow do I get started?

Begin building your industrial-grade embedded machine learning applications for the Thingy:53 today by following our getting started guide

  1. Purchase the Thingy:53.
  2. Connect the board to Edge Impulse.
  3. Follow the Edge Impulse's tutorial on:
  4. Deploy via the Edge Impulse Studio or via the nRF Edge Impulse iPhone and Android apps over BLE connection!
    • From the nRF Edge Impulse mobile application, select the Devices tab and connect to your Thingy:53, then select the Deployment tab to build and upload your Edge Impulse model to the Thingy:53.
    • From the Edge Impulse Studio, go to the Deployment tab of your Edge Impulse project, then build and download a ready-to-go binary that includes your machine learning model for the Thingy:53; or deploy as a C++ library and integrate the model into your own firmware!

Congratulations! You have now successfully built and deployed a low-power, industrial-grade embedded ML application for the Nordic Thingy:53.

Read the Refine and re-deploy your edge ML models over BLE with the Nordic nRF Edge Impulse mobile application sectionRefine and re-deploy your edge ML models over BLE with the Nordic nRF Edge Impulse mobile application

Drastically reduce your development time to a production-ready model by directly acquiring new sensor data, re-training/re-deploying your model, and streaming your model’s inferencing results over BLE from your Thingy:53 with the nRF Edge Impulse mobile application for iPhone and Android.

Follow the instructions in the Edge Impulse documentation to get started!

We are very excited to see what you build with the Thingy:53 and Edge Impulse. Please post any questions you have and any projects you create over on our forum or tag @EdgeImpulse and @NordicTweets on our social media channels!

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