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NRaha.1
Visitor II
October 27, 2021
Solved

STEVAL-STWINKT1 ML ON Microprocessor not ISM330DHCLX

I have a STEVAL-STWINKT1 board and I want to create a ML algorithm for the board to conduct predictive maintenance. However, I want my ML algorithm to run on the microprocessor and not on the ISM330DHCLX sensor. This is because, I realized that the ISM330DHCLX sensor is not sensitive to small changes in acceleration (around 0.1g), whereas the motor I am using is very small. Thus I want to use the IIS2DH sensor values as the input to my model instead.

My current workflow is I generate the ML UCF File using Unico, and then use the data logging function pack to flash the model to the STEVAL-STWINKT1 board and monitor its output. However, this workflow does not work if I want my ML algorithm to run on the STM32L4+ MCU itself instead of in the ISM330DHCX sensor.

Is there a step by step example on how I can do this?

    This topic has been closed for replies.
    TSand.1
    TSand.1Best answer
    Visitor II
    October 28, 2021

    Hi, you might consider to run the neural network on the STM32 using the X-Cube-AI tool, from which you have to set all the Sensortile.box project. or you might base on the FP-AI-SENSING1 package for already available examples.

    https://www.st.com/en/embedded-software/x-cube-ai.html

    https://www.st.com/en/embedded-software/fp-ai-sensing1.html

    Or alternatively you might use this tool (https://qeexo.com/) that supports the STEVAL-STWINKT1 board and with which you can easily acquire your data, train the NN and downloading the binary file for your tool.

    1 reply

    TSand.1
    TSand.1Best answer
    Visitor II
    October 28, 2021

    Hi, you might consider to run the neural network on the STM32 using the X-Cube-AI tool, from which you have to set all the Sensortile.box project. or you might base on the FP-AI-SENSING1 package for already available examples.

    https://www.st.com/en/embedded-software/x-cube-ai.html

    https://www.st.com/en/embedded-software/fp-ai-sensing1.html

    Or alternatively you might use this tool (https://qeexo.com/) that supports the STEVAL-STWINKT1 board and with which you can easily acquire your data, train the NN and downloading the binary file for your tool.