Category: PiPlanter

PiPlanter | Moisture detector and a few other updates

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Long time viewers will remember when this idea was conceived two Novembers ago, but essentially it’s a way to detect the relative moisture of a substance.

The principal is the same as in the above post, but this time, I made it bigger and attached it to a Raspberry Pi. The reason this is essential, is because I recently purchased a 12v DC pump capable of moving water. I will be able to sense the relative moisture in the plant, and then the plant will be able to water “itself”.

That will be done in python with the same basic technique I’ve been using all along, but in addition to gathering data about the plant every hour or so, it will be able to see if the plant needs water (by checking hopefully an array of moisture sensors) and then turning on the pump and watering it. I will also eventually integrate twitter and a webcam, but those cosmetic editions come once I know the system works.

To test it, I’ve added another set of data to the graph as seen in the last post and created a testing environment in my windowsill.

Basically I’ve put some dirt and 100mL of water into a container and inserted the sensor and am monitoring the moisture level over the next n hours, here are some pictures:

And here is a graph of some of the data:

I will make another post later today illustrating the process of plating the seeds.

Hey! This post was written a long time ago, but I'm leaving it up on the off-chance it may help someone. 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 | Basic package setup and bringing everything together

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I’m in a hotel trying to occupy myself with something interesting so I’ve decided to work on this. I had to re-image the SD card I’ve been developing this project on, but I saved to code so there’s no problem there. Now I need to re-install all the basic packages.

First I need to get the components of a LAMP server with the following commands:

Once you get the mysql server setup, you’ll need to create a database and tables in mysql.

To create the database you’ll be using run the following command:

And then grant the proper privileges to use later with the command:

Then we can enter the database and create a table:

Now we need to set up the specific libraries for python the first of which being spidev, the spi tool for the raspberry pi which we can grab from git using the following commands:

You also need to (copied from http://scruss.com/blog/2013/01/19/the-quite-rubbish-clock/):

As root, edit the kernel module blacklist file:

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

Save the file so that the module will load on future reboots. To enable the module now, enter:

We will also need WiringPi:

Then you need to get APscheduler, the timing program used to execute the incremental timing with the following commands:

You will need mysqldb to interface python and mysql:

Once you reboot, the following program should work:

And there you go! The program should log data every minute and then every hour to two different tables. To view those data sets as php tables you can use this php script:

Sometime later I’ll get to graphing the data.

Hey! This post was written a long time ago, but I'm leaving it up on the off-chance it may help someone. 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 | Using APScheduler to get timed samples in python

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I’m taking a “break” from my drone while I save some money to buy more tricopter parts, and since the weather’s getting nicer and nicer I’ve decided to start working on my PiPlanter again.

As a refresher, the PiPlanter is a Raspberry Pi powered garden. The goal is for it to just be able to be plugged in and add water to a water source and have the Pi monitor temp and moisture levels to be able to add more water as needed.

I’ve shown that is relatively easy to go from analog sensors to good looking tables and graphs using the raspberry pi, the problem that I ran into however was timing.

It became harder and harder to use the time.sleep function in python to handle long periods of time. When you are dealing with things like plants, you don’t need to water it very often, but for data’s sake, you should be polling the sensors a lot.

I’ve landed on the use of APScheduler in python, and here’s my source code:

[py]
#Timing setup
from datetime import datetime
from apscheduler.scheduler import Scheduler
import time

import logging #if you start getting logging errors, uncomment these two lines
logging.basicConfig()

#GPIO setup
import RPi.GPIO as GPIO
GPIO.setmode(GPIO.BOARD)

GPIO.cleanup()

pin = 26 #pin for the adc
GPIO.setup(pin, GPIO.OUT)
led1 = 11 #pin for the short indicator led
GPIO.setup(led1, GPIO.OUT)
led2 = 13 #pin for other long indicator led
GPIO.setup(led2, GPIO.OUT)

#the adc’s SPI setup
import spidev
spi = spidev.SpiDev()
spi.open(0, 0)

going = True

#fuction that can read the adc
def readadc(adcnum):
# read SPI data from MCP3008 chip, 8 possible adc’s (0 thru 7)
if adcnum > 7 or adcnum < 0:
return -1
r = spi.xfer2([1, 8 + adcnum << 4, 0])
adcout = ((r[1] & 3) << 8) + r[2]
return adcout

def rapidSample():
sampleTemp1 = (((readadc(0)*3.3)/1024)/(10.0/1000)) #this translates the analog voltage to temperature in def F
sampleLght1 = readadc(1)
samplePot1 = readadc(2)

GPIO.output(led1, True) #turns the led on
time.sleep(.1) #sleeps a little bit so you can see the LED on
print "Job 1", datetime.now(),"LDR:",sampleLght1 ,"Pot:",samplePot1,"Temp:",sampleTemp1 #prints the debug info
time.sleep(.1)
GPIO.output(led1, False) #turns the led off

def slowSample():
print "Job 2" , datetime.now()
GPIO.output(led2, True) #turns the led on
time.sleep(5)
GPIO.output(led2, False) #turns the led on

if __name__ == ‘__main__’:
#the following 3 lines start up the interval job and keep it going
scheduler = Scheduler(standalone=True)
scheduler.add_interval_job(rapidSample, seconds=1)
scheduler.add_interval_job(slowSample, minutes=1)
scheduler.start()
[/py]

This produces a loop that flashed a green led on and of for .1 seconds at a time per second, and then every minute, turns on a speaker and a red led for 5 seconds then turns it off. There are some images of what goes on below.

Here is a picture of the the print dialog in python:

You can see that the first job (green led) posts the values from the analog sensors every second

The second job (red led) just posts the time. But the function is expandable to do anything at any time.

Here are pictures of the board and the circuit in action:

Both LED’s off

The Green LED on, the red circled process in the printout

Here are both on

The next step is adding the mySQL in as seen in some other posts.

Hey! This post was written a long time ago, but I'm leaving it up on the off-chance it may help someone. 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 | Graphing With PHP 2

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This is a much more refined version of that graph I created earlier.

This one is much more detailed, and the sizes of the graph can easily be controlled with the imageSizeX and Y Vals.

This program will render:

This image:

And by modifying the values mentioned above to:

You will get this image:

Hey! This post was written a long time ago, but I'm leaving it up on the off-chance it may help someone. 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 | Interfacing an ADC, Python, and MySQL [Documentation]

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As this post is more of an update, I won’t be adding any explanations, just giving the python code.

This will read 3 values from the adc and put them into the database “adc_database”. It will put them in the table “adc_input_data_4” in the columns “Channel_1″,”Channel_2” and “Channel_3” respectively.

There you go, bigger post coming later tonight.

Hey! This post was written a long time ago, but I'm leaving it up on the off-chance it may help someone. 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.