I have tried this with Ethanol and Air sucessfully. I have a tutorial with data/models and python code here: https://github.com/mcalisterkm/teach-your-pi-to-sniff-with-bme688 If the model that AI studio builds has a high degree of discrimination, I can't see why it would not work the same with a breakout board (PI3G, Pimoroni, Adafruit, etc ). Are you using BSEC 2.4.0 ? AI-Studio and BSEC are not at the same version, and you need to be sure of a supported mix, there is a table in my tutorial which lists current versions. I am surprised you had any sucess recording training data with a single sensor, and sucessfully generating a model in AI-Studio. The PI3G bmerawdata.py has multiple problems (file naming, data structure, etc) that prevent a sucessful model being built. Using the 8 sensor dev-kit is the way to go. Using a model on a single sensor is relatively easy. One thing to bear in mind is that a model is specific to the data set, in my case I recorded Ethenol is high concentrations. When I used the model to detect low concentrations it mis-categorized it. With more data collection to cover a wider range of scenarios I am sure I could have generated a model with better results across a wider range of concentrations. In your case you are trying to detect an oil mist, that could be something that fouls the sensor - touching the sensor contaminates it requiring cleaning.
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