I wasn’t originally going to post about this, but I’m so excited I couldn’t not share. I’ve recently been collecting data for a “garduino,” an automatic plant-watering device based on an Arduino. The idea is to use the data to characterize the system for a feedback controller – but I’ll post separately on that later. For now, check out this data:
At first glance, you can clearly see by the large spikes when I watered the plant. You can also see that the moisture level decays exponentially following watering times – to be expected based on settling, evaporation, and plant uptake. But you can also see these little bumps where the exponential curve “reinitiates” – these occur mostly on days when I didn’t water the plant (rosemary, if you’re curious), and closely correspond with the times when I would have watered it otherwise. What’s going on here?
This puzzled me for a while – until I remembered something my roommate had said when I started this project. He told me that, based on his reading, most plants do best if watered once per day, in the morning. Bearing that in mind, the most likely explanation I can think of is that the plant’s water uptake increases in the morning – briefly, but enough that it creates a noticeable pattern in the data. I don’t know whether it does this naturally (based on light patterns?), or if it has “learned” my watering schedule, but either way, I think it’s pretty cool!