Beer IoT (Part 5)
Welcome back for part five of the fermentation instrumentation series. In part four, I placed a few different sensors in some actively fermenting beer to gather data. I now have a few days of pressures and force vectors to analyze …
… but I’m not quite ready to share it all yet. There are some things that look promising, but mainly still a fair bit of confusing. I think there are a couple of quick tests I can run after emptying the carboys that will move some things out of the confusing pile and toward either confirmation or rejection. So, I’m going to delay writing those posts until I can do less handwaving.
To tide you all over until then, I thought I’d share some quick insights from the sensor data that I do not expect to be closely tied to specific gravity: temperature. I have two temp sensors collecting readings: one on a Helium Atom outside the carboys, and one packaged with the pressure sensor submerged in beer at the bottom of a carboy. Let’s start with the one outside the carboy:
This graph tracks the air temperature a few inches from the carboy. It’s basically the air temperature of my kitchen/dining-room. And from it, you can nearly read my life. The temperature drops initially as my kitchen cools after brewing. It rises in the morning as we make brunch, and again in the evening as we make dinner. The spike at 8am Tuesday morning is not breakfast. That is the residual heat from my hand as I held the Atom to connect USB power. The cooling into Wednesday morning is the clouds breaking and the weather temperature dropping.
But there’s something even more fun going on here: the light region around the dark line marks the min/max of the readings. Why is the max so much higher? Enhance.
Where did this sawtooth come from? Clue 1: there are exactly six teeth per hour. Clue 2: I queue up readings for ten minutes, and then send them to the cloud all at once. My bet is that I’m picking up residual heat from that extra work. Looking at my code, I forgot to power down the sensors until after I sent all the data to the cloud. Let’s fix that, and then recheck:
The sawtooth until 11am is what we saw earlier. The jump between 11 and 12 is heat from my hand as I plug in the USB cable again. And then … hmm, same sawtooth. Maybe this is heat from the radio instead. It’s a tenth of a degree Celcius, nothing to worry about, but an interesting artifact.
So, what about the temp sensor in the beer?
Ah, yes, that would be the effect of being surrounded by sixteen pounds of water. It doesn’t change temperature quickly. This works out in the beer’s favor: yeast really don’t like quick temperature changes. Giving them time to adapt keeps them healthy and fermenting.
Here are both temperatures overlaid, so you can compare directly (with bonus 24+ hours on the end):
My apologies for starting with the data you’re all less interested in. It’s too interesting not to share something, but there are too many questions about the other samples to tell a coherent story yet. The data you’re really interested in will be up after bottling, and I’ll share the raw data at that time as well, so you can do your own analysis.
Update: the first set of data, from the BeerBug, is now up in part six.