So in my last posting of the PiPlanter source code, the python script alone was 500 lines long. The intent with was to make things more modular and generic compared to the original version of the code that ran two years ago. Since the project has expanded a considerable amount since two summers ago, my goal of keeping everything short and concise isn’t really valid anymore so I’ve decided to split the code up into modules.

This improves a number of things, but it makes it kind of inconvenient to simply paste the full version of the source into a blog post. To remedy this, I’ll be utilizing www.esologic.com/source, something I made years ago to host things like fritzing schematics.

The newest publicly available source version can be found here: https://esologic.com/source/PiPlanter_2/ along with some documentation and schematics for each version to make sure everything can get set up properly. What do you think of this change? Will you miss the code updates in the body text of a blog post?

With all that out of the way, let’s talk about the actual changes I’ve made since the last post.

The first and foremost is that using Pillow, I’ve added a way to overlay text onto the timelapse frames like so:

Before

Ambient Light: 27.1%, Ambient Temp: 47.0DF, Average Plant Mst: 0.0% http://t.co/YqLJkOJ2FG pic.twitter.com/Ms2nk6OLAo

— piplanter_bot (@piplanter_bot) November 21, 2014

After

 

Ambient Light: 73.3%, Ambient Temp: 54.5DF, Average Plant Mst: 23.7% http://t.co/YqLJkOJ2FG #PiPlanter pic.twitter.com/QocHKcTE55 — piplanter_bot (@piplanter_bot) November 22, 2014

This was prompted by some strange behavior by the plants I noticed recently seen here:

I thought it was strange how the chive seemed to wilt and then stand back up and then wilt again, it would have been nice to be able to see the conditions in the room to try and determine what caused this. Hopefully I can catch some more behavior like this in the future.

Here is the new Image function with the text overly part included if you’re curious:

Now that I’ve got the PIL as part of this project, I’ll most likely start doing other manipulations / evaluations to the images in the future.

Okay! Thanks for reading.

Ten days ago I finished installing the third ever instance of the PiPlanter in a lab in the physics department at my college! I went with the the rack mounted design as I did this past summer, and am going to be growing Basil, Cilantro and Parsley as opposed to tomatoes. Here are some photos of the new setup:

There are a few major changes that come with this new instance. The first and foremost being the addition of LED grow lights. I’ll post a new version of the code with LED routines included when I think it’s polished enough. The second difference is that a tray of soil is being used as the growth medium for the plants as opposed to pots of soil. This will more than likely be the configuration I use moving forward. The final difference is the actual type of plants being grown. I’m moving away from tomatoes because there will be nothing to pollinate the flowers in the winter as well as the fact that I cook a lot and it will be neat to have spices that I can use on a day to day basis.

The first 10 days of growth has gone well. Here’s a video of them growing so far:

Thanks for reading!

The CANSPI board is a nice integration of the MCP2515 CAN Bus Controller and the MCP2551 CAN Bus Transceiver. To interface with these boards I’m using an Arduino Nano and the Seeed Studio CAN Bus Shield Library.

Here are some photos of the configuration, including the switch position on the CANSPI being used:

The wiring diagram goes as follows:

There are two parts of Arduino code, the sender and the receiver. The following code sends a sample piece of CAN data. Attach a potentiometer to A0, and twist it to see the differences in data in the receive code:

The following prints all CAN data received to the serial monitor:

Twist the potentiometer and see the change in data to see that it’s all working:

Thanks for reading!

Since I returned to college the PiPlanter has been running without me having to do any maintenance on it at all. The plants are still alive and growing and all processes associated with the PiPlanter are still going. I figure now is a good a time as any to bring together all of the work I’ve done to till this point in one concise post.

This does NOT mean I’m done working on future versions of the PiPlanter. I’ll hopefully write another post stating goals for the future sometime soon. Now onto the build tutorial.

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The Hardware

 

First, the hardware of the project. A good place to start would be the parts list:

In the previous version of the PiPlanter, I didn’t have a concrete parts list for the project. Hopefully I’ll be able to keep this spreadsheet updated if the project changes. A lot of these components are mix and match, you could use pretty much any pump (The math for volumetric pumping is done with this pump) or any tubing or any power supply that can do 12v and 5v. A computer PSU would work great as well.

This is the hookup guide for the system:

(Thanks to tamps for the help!)

The two sets of header blocks are to be replaced by the moisture sensors, and the motor replaced with the pump.

For a physical configuration, I’ve found through multiple times doing this that mounting it on a wire rack works the best as seen here:

Edit (10/19/2014) Here is the same group of plants two months later without any direct human interaction. They grew from the light in the window and used up all of the water in the reservoir which was totally filled before I left.

To distribute the water to the plants, attach the vinyl tubing to the outflow of the pump and seal off the other end of the outflow tube. Run the tubing along the plants and drill holes wherever you’d like the water to exit.

You’ll also need to install the camera module in the Pi and point it wherever you’d like the frame of the photo to be.

 

The Software

As a preface, I’d like to at first say that this software was written entirely by me. I’ve never had any formal training in programming of any kind, so if there are obvious flaws with my code please let me know. That being said, I’ve found that this system is very effective and has worked for me and kept my plants alive for months.

All of this runs off of a base install of raspian on a raspberry pi model b.

There three major parts to the software. First, the prerequisites:

You’ll need to enable SPI on your Pi in order to use the MCP3008 ADC. Do this by running the following commands:

Comment out the spi-bcm2708 line so it looks like this:

Then run this to make it more permanent.

And finally reboot your Pi with:

Then the php code that renders the pChart graph. More details for installing pChart here and officially here.

And now the star of the show, the python script:

Before running, make sure you make the following changes to the script:

You’ll need set up access to twitter API’s, seen here. You’ll need to input your information about your twitter app into into 331-334 of this script.

You’ll need to input information about your YouTube account on line 429

On line 473 you’ll need to input your mysql information.

 

Output Demos

The PiPlanter is very connected. It renders graphs of data, takes images and renders timelapse videos.

Here’s a standard tweet showing the plants:

Ambient Light: 86.6%, Ambient Temp: 66.1DF, Average Plant Mst: 90.9% http://t.co/U75XO1EUvG pic.twitter.com/gtj2VeoFOT

— piplanter_bot (@piplanter_bot) September 11, 2014

Here’s a tweet showing a day’s worth of data in  a  graph render:

Graph of day so far: Moisture % – Blue, Ambient Light % – Yellow, Temp DF – Red http://t.co/U75XO1EUvG pic.twitter.com/fEbnicWN2j — piplanter_bot (@piplanter_bot) September 11, 2014

Here’s a tweet showing a week’s worth of data in a graph render:

Graph of Previous Week: Moisture % – Blue, Ambient Light % – Yellow, Temp DF – Red http://t.co/U75XO1EUvG pic.twitter.com/oGAHyh9vB1

— piplanter_bot (@piplanter_bot) September 11, 2014

Here’s a timelapse video of three days:

Follow @PiPlanter_Bot for updates on my plants.

That’s pretty much it! Please feel free to modify this code for any use you’d like.

All of my research on this project can be found here.

Thanks for reading, and please leave a comment if you like my work!