EYE on NPI - Bosch BME688

3 роки тому

This week's EYE ON NPI smells so sweet, it's the BME688 digital nose gas sensor from Bosch! (www.digikey.com/en/product-hi...) The BME680 is a very nice gas sensor released a few years ago, and remains the only temperature-humidity-pressure-gas sensors that we've ever seen. Small and easy to use, at Adafruit we've sold tens of thousands of BME680 sensors on breakout boards so we're very excited to see the next-generation of BME68x chips arriving and in stock at Digi-Key.
The BME688 is completely back compatible to the BME680, in fact over the weekend we added support to the latest Bosch C API (github.com/adafruit/Adafruit_...) So, like the BME680 you get a high-grade temperature, humidity and pressure sensor that can measure humidity with ±3% accuracy, barometric pressure with ±1 hPa absolute accuracy, and temperature with ±1.0°C accuracy. Because pressure changes with altitude, and the pressure measurements are so good, you can also use it as an altimeter with ±1 meter or better accuracy!
I'm going to order some ASAP to turn into a breakout board, it looks like this chip is fully pin-compatible with the BME680 so if you need an example circuit that we know works, check out our open source BME680 design. (github.com/adafruit/Adafruit-...) If you're looking for a great all-in-one sensor, and particularly if you've been using the BME680 and want to upgrade, there's thousands of BME688 stock at Digi-Key right now at a great price! (www.digikey.com/short/0vjw0b8q) Order today and you will be smelling success by tomorrow afternoon.
See on Digi-Key at www.digikey.com/short/0vjw0b8q
Bosch Video • How gas sensing gets i...

КОМЕНТАРІ: 6

@rpavlik1 3 роки тому

Oh nifty! So now the real question: how hard would it be to reproduce their ML closed source thing with open source? Interesting to learn how these metal oxide sensors actually manage to be made for all those different gases.

@Sparkletron 5 місяців тому

Very cool that you can train your BME688 to recognize a particular VOC. But assuming you are either unable or unwilling to do that, what value is the BME688 over the BME680 right out of the box? It would be nice if these training profiles were already available, and you could just select the ones of interest.

@youjean83 2 роки тому

I was about to get me the 680 then this video was recommended to me by the holy youtube algorithm. I wonder if there's any collection for different data profiles available somewhere? Similar to TensorFlow?

@ayourk1 Рік тому

I could see this being used as a sort of Carbon Monoxide sensor in a custom thermostat.

@bewingbewing 3 роки тому

I'd be interested to know what that 93% represents. I.e., what gave the false positives? Was it immersed in jars of ... empty? water? chocolate?

@jon_cook 3 роки тому

93% is the accuracy of the model which is actually very good. When you train a model you give it training data to train with and then validation data that it's never seen before the test against. So when it evaluated the validation data it was able to tell what it was 93% of the time. Pretty much the other 6% or so it either classified it as something else that it was trained to classify or maybe it classified it as unknown.