LLMs are already used in signal processing so the idea is explored.

Simply put anything that can be encoded is a language, so you just need sensors to capture and classify the incoming data and build that into a model. The real question is post training the model to behave correctly as these places are far less explored than things at the human scale. RLHF may be a poor choice because the models may see actual behaviors that humans don't and humans will discount it as being incorrect.