Hi team,
I have a quick suggestion request. I am planning to use BME688 to sense various gases e.g., ammonia with help of a custom trained AI/ML model. Sure, it will require a bit of ML model training efforts but looks a lot better option as compared to MQ137 in terms of quality and power use. Any opinion/feedback?
Hey Riddhi,
Welcome back!
It seems like you’ve got an awesome project in the works! I think that using the BME688 is advantageous when using it for an AI/ML use case, it will be able to detect multiple gases at the same time and hopefully you can train the model to effectively interpret that data.
I wish you the best of luck with the project and make sure you keep us up to date on how it goes!
Cheers,
Blayden
Hi Riddhi,
I had a quick look at the presentation Adafruit gave on using the machine learning with that sensor (linked here for anyone else interested later) and it sounds like a huge step up from your basic analog sensor that has to be calibrated for a single setup.
Being able to train multiple sensors with the demo code to detect a target scent and extracting the preferred sensor settings first try rather than trial and error through a bunch of options is a win.
Yeah. I think you can proceed with BME688. It is better than MQ sensors at least for ML based projects.
And you can get our latest projects and tips straight away by following us on:
