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This software pack enables developers to develop and deploy neural networks on MCU-based systems for building smart sensing applications. This example shows how to use ML to create a fan vibration state monitoring solution.

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Application Software Pack: ML State Monitor

This repository holds the ML State Monitor App SW Pack and depends on the MCUXpresso SDK overall delivery.

Assemble the application

You need to have both Git and West installed, then execute below commands to gather the whole APP-SW-PACKS/ML-State-Monitor delivery at revision ${revision} and place it in a folder named appswpacks_ml_state_monitor.

west init -m https://github.com/NXPmicro/appswpacks-ml-state-monitor --mr ${revision} appswpacks_ml_state_monitor
cd appswpacks_ml_state_monitor
west update

Replace ${revision} with any SDK revision you wish to achieve. This can be mcux_release_github if you want the latest state, or any commit SHA.

Build and run the application

To build and run the application please refer to the Lab Guide or check the steps in Run a project using MCUXpresso IDE.

Other reference applications

For other rapid-development software bundles please visit the Application Software Packs page.

For SDK examples please go to the MCUXpresso SDK and get the full delivery to be able to build and run examples that are based on other SDK components.

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This software pack enables developers to develop and deploy neural networks on MCU-based systems for building smart sensing applications. This example shows how to use ML to create a fan vibration state monitoring solution.

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