I am Curious if anyone here has integrated AI concepts into embedded projects using FreeRTOS?

Kernel
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Hey folks,

I have been experimenting with FreeRTOS on a couple of STM32 projects & got curious—has anyone tried blending any kind of lightweight AI models or inference capabilities into their RTOS-based setup?

I am not talking about full-blown neural networks but maybe using something such as TinyML or even basic decision trees within tasks to make the system “smarter.” want to hear about how you handled memory constraints, scheduling or even basic data collection in such setups.

Also, I started a Generative AI Course just out of curiosity and it sparked the idea—what if we could apply even a fraction of that logic in microcontroller projects? Not practical maybe but definitely interesting.

Thank you.:slight_smile:

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Hi Sofiaya,
Here is a video from Embedded World 2021 that covers a tinyML project using FreeRTOS https://www.youtube.com/watch?v=YJjxjozCJjA.

If you wanted to interact with bigger models, it would probably make more sense (and only be feasible) to interact with it over the internet. You could use coreHTTP to make HTTP requests to a server hosting a bigger model for example. This video shows how you can setup your own model in AWS bedrock and interact with it through invoking a lambda from API gateway https://www.youtube.com/watch?v=aMAmD-1SFYQ. You could of course interact with any consumer AI that has an HTTP API.

Hope this helps.

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