PiPlanter | Bringing most of it together

Last night I finished the majority of the software for this project. Here’s a video of me going over what happened and what the program does in simpler terms:

Essentially, every hour, the raspberry pi samples data from 4 humidity probes, an LDR and a tmp sensor. Once the sampling is complete, it dumps the data into a mysql database. From there the data is rendered into a graph using pChart┬áin the form of a .png image. From there, that .png files is uploaded to flickr using this api. Once the file is uploaded, it returns it’s photo ID to the python script. From there, a tweet is built containing the brightness at the time of the tweet, the temperature at the time of the tweet, and the average moisture of the plants. It also uses the photo ID from flickr obtained earlier to build a URL leading to that image on flickr which it tweets as well. The final part of the tweet is a url that leads to this post!

That was a lot of explanation, but this program does quite a bit. The source comes in two parts, here’s the python script that handles the brunt of the processing. You will need a bunch of libraries to run this, you could pick through past posts of mine to find what those are, but when I do a final post for this project I will include all of those.

Here’s the .php script that renders the graph from the mysql data. It is called by the python script.

Thanks for reading!

Hey! This post was written a long time ago, but I'm leaving it up on the off-chance it may help someone, but proceed with caution. It may not be a good idea to blindly integrate this code or work into your project, but instead use it as a starting point.

PiPlanter | Second round of data collection

So as I said in one of my previous posts, I am going to be collecting a lot of data over the next few weeks while the tomato plants grow. I will be doing this to determine when soil is “dry” and how temperature and light effect that process. For the last week I have been collecting data in the configuration seen in my last post and here is the graph it produced you can click to see the full image:

This graph proves a few things. The first thing is that the relative moisture sensor works. As one can intuitively understand, if you don’t add more water into the system, nature will remove water via evaporation. The overall trend of the blue line (the rel mst sensor) is downward, backing up this point.

The problem with this setup was that I was spitting the voltage across the two probes constantly, which along with the water caused the nails to rapidly oxidize, which is something I would like to avoid in the long term. This also may have seriously corrupted the data so besides general trends, this whole set is unusable.

This isn’t necessarily a bad thing though, as I wanted to conduct a second trial with more probes and more dirt.

I decided to go with 4 probes, and here are a few pictures of the assembly process. Assembly process is the same, I just did it at my school:

I cut it into 3cm sections and then drilled holes on the midpoints of the 2nd and 3rd cm as seen in a photo below.

Here are the holes drilled for the nails

Here are the nails inserted into all 4

Here is the wire wrapped around the nail

Once solder is applied, the connection is very strong and conductive

Here’s the gluing process

Here are all of the sensors assembled. I attached headers to the other ends as seen in the last post.

Since i’m using 4 sensors now, and to get around the oxidation problem, I added a NPN transistor to cut the ground current when the sensor isn’t being used so it only turns on when it’s getting polled. Here is the new python code:

It’s pretty much the same thing.

The graph is also very similar, but I won’t post that code as it’s not different enough.

Here are pictures of setting up the whole system:

I used the same soil as seen in the previous post, and added 125mL of water to each sample.

Here’s a video of me explaining the whole process:

Once enough data is collected I’ll post a graph of it here.

Hey! This post was written a long time ago, but I'm leaving it up on the off-chance it may help someone, but proceed with caution. It may not be a good idea to blindly integrate this code or work into your project, but instead use it as a starting point.