PiPlanter
PiPlanter is a self-monitoring plant growing robot powered by Raspberry Pi. The project is the brainchild of Devon Bray at EsoLogic, who generously provides the base code, schematic and instructions to create the system.
April 2016 update - new seeds, new irrigation system, new location! Read more.
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The PiPlanter has succesfully started growing three plant varieties (July 12, 2015).
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Plants sprouting in the JG PiPlanter on July 12, 2015, with my robot helpers Wall-E and Eve.
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Wall-E tends to some Italian basil.
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A Raspberry Pi B+ monitors the plants, takes photos and tweets every hour.
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Photocell (left), soil moisture sensors (bottom left), and temp sensor (middle left). In the middle, an ADC translates everything. The MOSFET (right) controls the pump.
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This home-made sensor monitors and controls water levels. An ADC converts the voltage between the two nails into a soil moisture reading.
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This water pump activates any time the soil moisture dips below 30%, pumping 2.5 liters into the plants from the reservoir below.
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This PiCamera takes a photo of the plants every 20 minutes. The Pi tweets photos every hour, and once every three days it creates a time-lapse video of the plant growth.
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Three plant varieties are currently growing in the planter - thyme, red basil and Italian basil.
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PiPlanter from above.
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The JG PiPlanter on July 12, 2015.
- Measures ambient light levels, air temperature, and soil moisture every 20 minutes.
- Takes a photo and tweets (@jg_piplanter) the photo and measurements every hour on the hour.
- Generates and tweets a chart of the day's data once every three hours. (3-6-9 a.m., noon, 3-6-9 p.m., midnight)
- Once per day, it tweets a 24-hour chart of the data. (10 p.m.)
- Every three days at midnight, it posts a time-lapse video of PiPlanter growth to Youtube. It also tweets a week-to-date metrics chart (see below).
- Finally, every 20 minutes, the PiPlanter checks to see if the soil moisture has fallen below 30%. If it has, it waters the plants and tweets a notification.
The PiPlanter is currently growing thyme, red basil, and Italian basil.
The program is written in Python, except for the PHP to generate the charts. Download my code here.
The Raspberry Pi utilizes Tweepy, apscheduler, youtube-uploader and pChart2.0.
Data is collected with one TMP36GT9Z-ND temperature sensor, one PDV-P9007-ND photocell and two homemade soil moisture sensors (instructions again provided by Devon here).
Graph of Week So Far: Moisture % - Blue, Light % - Yellow, - Red http://t.co/NvqcNZhy0F pic.twitter.com/F8LaYA8U1c
— JG PiPlanter (@jg_piplanter) July 12, 2015Follow my PiPlanter updates at @jg_piplanter!
Ambient Light: 74.0%, Air Temp: 76.0F, Average Soil Mst: 46.8% http://t.co/NvqcNZhy0F pic.twitter.com/Ebe1wyfnZG
— JG PiPlanter (@jg_piplanter) July 12, 2015Thanks again to Devon Bray at EsoLogic, and to my wife Taylor for challenging me to such a cool project. Pesto for days!
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