This post is many months in the making and I am very proud of the thing’s I’ve done here, and very thankful to all of those (specifically at www.reddit.com/r/raspberry_pi) who have helped me along my way to getting this project up and running.

This page contains every single post related to this project, please feel free to go back and look at my progression and pick up tips along the way if you want to try something like this.

Let’s get this going, here’s an overview video:



There are 8 parts to this system and, you guessed it, I’ll be going in-depth about every single one!

Sensor Network

So at it’s core, the PiPlanter is a Sensor Network & Pump System. Here’s a video explaining the sensor array:

This project uses a TMP35-37 sensor to get a pretty precise temperature reading of the room. Later down in this post you can find out the algorithm to determine the temperature in Fahrenheit. It also uses a basic LDR to get the relative ambient light level in the room. Along with those two sensors, there are 4 relative humidity sensors of my own design, here’s a picture of them as seen in this post:

They’re hooked up to the ADC (mentioned later) in the same way that the LDR is, with a voltage dividing resistor, and then fed directly into ADC. The principal behind this sensor is that when you insert it into soil, the water in that soil connected the two probes, causing a voltage to flow across them. So if there is more water in the soil, more electrons will flow across them, and the analog value will be higher. It’s very basic, but it works. I’ve done several long term tests, and over time, as the soil becomes dryer, the value gets lower, indicating relative dryness. Here is a picture of the four probes in the soil, with the plants.

The TMP sensor’s output is plugged directly into the ADC and the LDR is very basically connected to the ADC as well, this is essentially how how the whole thing is setup on the breadboard:

Pump System

The pump system is pretty dead simple. Essentially it is a PowerSwitch Tail II switching the mains to a 9v DC power supply. The 9v power supply is connected directly to a 12v DC submersible pump. Instead of using a motor driver chip, which requires 3 pins to do, and the chip would get hot and whatnot, I’ve decided to go with this method.

The pump is not self priming. This means it cannot make the transition from pumping air to pumping water. I wrestled with this problem for a long time, and came up with what I think is an elegant solution. I submerged the pump directly into the water, which means the pump will never fill with air, and will always pump water when activated. Here’s a video explaining the pump system:

Raspberry Pi ADC

The next system is the ADC connected to the Raspberry Pi. It is an 8 bit, 8 port analog to digital converter that can easily run on 3.3v so it’s perfect for the pi. Here is the chip, and you set it up as follows (I took this from an earlier post I wrote)

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:

sudo apt-get install git git clone git://github.com/doceme/py-spidev cd py-spidev/ sudo apt-get install python-dev sudo python setup.py install 1 2 3 4 5 sudo apt - get install git git clone git : / / github .com / doceme / py - spidev cd py - spidev / sudo apt - get install python - dev sudo python setup .py install

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:

sudo vi /etc/modprobe.d/raspi-blacklist.conf 1 sudo vi / etc / modprobe .d / raspi - blacklist .conf

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

#blacklist spi-bcm2708 1 #blacklist spi-bcm2708

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

sudo modprobe spi-bcm2708 1 sudo modprobe spi - bcm2708

To read from the ADC, add the following to your python code. The full code will be listed later:

#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 1 2 3 4 5 6 7 8 #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

So just use “readadc(n)” to get a value.

Python Code

I’ve made a real effort this time to comment my code well, so I’m not going to do a line by line breakdown like I often do, but I will clearly state the installs and setup things as follows. I’m assuming you have python-dev installed.

Download and install: APScheduler, this is a very straight forward install

Download and install: tweepy, you will need to go through the API setup process.

Download and install: flickrapi, you will need to go through the API setup process.

Here’s the source code for the python component of this project:

#Timing setup from datetime import datetime from apscheduler.scheduler import Scheduler import time import datetime import sys import os now =datetime.datetime.now() #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) NPNtrans = 3 #the pin for the npn transistor GPIO.setup(NPNtrans, GPIO.OUT) sampleLED = 5 #the indicator LED GPIO.setup(sampleLED, GPIO.OUT) pump = 7 #pin for the pump GPIO.setup(pump, GPIO.OUT) #the adc's SPI setup import spidev spi = spidev.SpiDev() spi.open(0, 0) #sets up the program's ability to write to a mysql database import MySQLdb con = MySQLdb.connect('localhost','piplanter_user','piplanter_pass','piplanter'); cursor = con.cursor() #tweepy setup, you must use the keys given to you when you create your app import tweepy consumer_key="" consumer_secret="" access_token="" access_token_secret="" #"logs in" to twitter, auth = tweepy.OAuthHandler(consumer_key, consumer_secret) auth.set_access_token(access_token, access_token_secret) api = tweepy.API(auth) #Flickr Setup import flickrapi api_key = '' api_secret = '' flickr = flickrapi.FlickrAPI(api_key, api_secret, format='json') (token, frob) = flickr.get_token_part_one(perms='write') if not token: raw_input("Press ENTER after you authorized this program") flickr.get_token_part_two((token, frob)) #Variable Setup ontime = 20 #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 slowSample(): date0 = "21-06-2013 15" date1 = "25-06-2013 12" date2 = "29-06-2013 12" date3 = "04-07-2013 12" date4 = "06-07-2013 12" if str(time.strftime('%d-%m-%Y %H')) == date0: water() if str(time.strftime('%d-%m-%Y %H')) == date1: water() if str(time.strftime('%d-%m-%Y %H')) == date2: water() if str(time.strftime('%d-%m-%Y %H')) == date3: water() if str(time.strftime('%d-%m-%Y %H')) == date4: water() print "----------start----------" GPIO.output(NPNtrans, True) GPIO.output(sampleLED, True) time.sleep(1) sampleTime = time.ctime() mst1 = readadc(0) mst2 = readadc(1) mst3 = readadc(2) mst4 = readadc(3) pot1 = readadc(4) ldr1 = readadc(5) millivolts = readadc(6)*(3300.0/1024.0) temp_c = ((millivolts - 100.0)/10)-40.0 tmp1 = (temp_c * 9.0 / 5.0) + 32 #prints debug info to console print sampleTime,"|","MST1:",mst1,"MST2:",mst2,"MST3:",mst3,"MST4:",mst4,"Pot1:",pot1,"LDR1:",ldr1,"TMP1:",tmp1 #prints the debug info #adds the data to the mysql table cursor.execute("INSERT INTO piplanter_table_17(Time,mst1_V,mst2_V,mst3_V,mst4_V,pot1_V,ldr1_V,tmp1_F) VALUES(%s,%s,%s,%s,%s,%s,%s,%s)",(sampleTime,mst1,mst2,mst3,mst4,pot1,ldr1,tmp1)) con.commit() #this is important for live updating GPIO.output(NPNtrans, False) #turns the probes off #renders the image of the graph print "render start" os.system("php /opt/bitnami/apps/wordpress/htdocs/piplanter/renderScript.php") #renders the .png file print "render complete" #finds the newest image in the directory allfiles = sorted(os.listdir('/opt/bitnami/apps/wordpress/htdocs/piplanter/renders/'), key=lambda p: os.path.getctime(os.path.join('/opt/bitnami/apps/wordpress/htdocs/piplanter/renders/', p))) newest = '/opt/bitnami/apps/wordpress/htdocs/piplanter/renders/'+allfiles[-1] print 'File for upload: ' + newest #prints location and file to console response = flickr.upload(filename=newest, title=sampleTime, format='etree') #uploads the file to flickr photoID = response.find('photoid').text #gets the id of the photo for constructing a url print 'Upload Successful, Photo ID: ' + photoID #more debug info #tweets the image and data send = 'Brghtnss: ' + str(format((((float(ldr1)/1024)*100)),'.0f')) + '% / ' + 'Tmprtr: ' + str(format(tmp1,'.0f')) + ' Dg F' + ' / Avg Plnt Moisture: '+ str(format(float((float((mst1+mst2+mst3+mst4)/4)/1024)*100),'.0f')) + '%' + ' Graph: ' +'http://www.flickr.com/photos/97350286@N08/'+photoID +' - www.esologic.com/?p=643' #builds the text of the tweet print "Tweeting:" , send #for debug purposes api.update_status(send) #tweets the tweet time.sleep(.1) GPIO.output(sampleLED, False) print "-----------end-----------" def water(): print "===== Starting Watering Process =====" GPIO.output(NPNtrans, True) GPIO.output(sampleLED, True) time.sleep(1) sensor1_before = readadc(0) sensor2_before = readadc(1) sensor3_before = readadc(2) sensor4_before = readadc(3) before = "WATERING START / Moisture Before - " + "Sensor 1:" + str(sensor1_before) + " Sensor 2:" + str(sensor2_before) + " Sensor 3:" + str(sensor3_before) + " Sensor 4:" + str(sensor4_before) + " - Average:" + str((float(sensor1_before+sensor2_before+sensor3_before+sensor4_before)/4)) api.update_status(before) print before GPIO.output(pump, True) time.sleep(ontime) GPIO.output(pump, False) time.sleep(60) #gives the water time to penetrate the soil sensor1_after = readadc(0) sensor2_after = readadc(1) sensor3_after = readadc(2) sensor4_after = readadc(3) after = "WATERING COMPLETED / Moisture After - " + "Sensor 1:" + str(sensor1_after) + " Sensor 2:" + str(sensor2_after) + " Sensor 3:" + str(sensor3_after) + " Sensor 4:" + str(sensor4_after) + " - Average: " + str((float(sensor1_after+sensor2_after+sensor3_after+sensor4_after)/4)) api.update_status(after) print after GPIO.output(NPNtrans, False) GPIO.output(sampleLED, False) print "====== Watering Process Complete =====" #water() slowSample() #runs the sample once before the interval starts, mostly a debug function scheduler = Scheduler(standalone=True) scheduler.add_interval_job(slowSample, hours=1) scheduler.start() #runs the program indefianately once every hour 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 #Timing setup from datetime import datetime from apscheduler . scheduler import Scheduler import time import datetime import sys import os now = datetime . datetime . now ( ) #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 ) NPNtrans = 3 #the pin for the npn transistor GPIO . setup ( NPNtrans , GPIO . OUT ) sampleLED = 5 #the indicator LED GPIO . setup ( sampleLED , GPIO . OUT ) pump = 7 #pin for the pump GPIO . setup ( pump , GPIO . OUT ) #the adc's SPI setup import spidev spi = spidev . SpiDev ( ) spi . open ( 0 , 0 ) #sets up the program's ability to write to a mysql database import MySQLdb con = MySQLdb . connect ( 'localhost' , 'piplanter_user' , 'piplanter_pass' , 'piplanter' ) ; cursor = con . cursor ( ) #tweepy setup, you must use the keys given to you when you create your app import tweepy consumer_key = "" consumer_secret = "" access_token = "" access_token_secret = "" #"logs in" to twitter, auth = tweepy . OAuthHandler ( consumer_key , consumer_secret ) auth . set_access_token ( access_token , access_token_secret ) api = tweepy . API ( auth ) #Flickr Setup import flickrapi api_key = '' api_secret = '' flickr = flickrapi . FlickrAPI ( api_key , api_secret , format = 'json' ) ( token , frob ) = flickr . get_token_part_one ( perms = 'write' ) if not token : raw_input ( "Press ENTER after you authorized this program" ) flickr . get_token_part_two ( ( token , frob ) ) #Variable Setup ontime = 20 #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 slowSample ( ) : date0 = "21-06-2013 15" date1 = "25-06-2013 12" date2 = "29-06-2013 12" date3 = "04-07-2013 12" date4 = "06-07-2013 12" if str ( time . strftime ( '%d-%m-%Y %H' ) ) == date0 : water ( ) if str ( time . strftime ( '%d-%m-%Y %H' ) ) == date1 : water ( ) if str ( time . strftime ( '%d-%m-%Y %H' ) ) == date2 : water ( ) if str ( time . strftime ( '%d-%m-%Y %H' ) ) == date3 : water ( ) if str ( time . strftime ( '%d-%m-%Y %H' ) ) == date4 : water ( ) print "----------start----------" GPIO . output ( NPNtrans , True ) GPIO . output ( sampleLED , True ) time . sleep ( 1 ) sampleTime = time . ctime ( ) mst1 = readadc ( 0 ) mst2 = readadc ( 1 ) mst3 = readadc ( 2 ) mst4 = readadc ( 3 ) pot1 = readadc ( 4 ) ldr1 = readadc ( 5 ) millivolts = readadc ( 6 ) * ( 3300.0 / 1024.0 ) temp_c = ( ( millivolts - 100.0 ) / 10 ) - 40.0 tmp1 = ( temp_c * 9.0 / 5.0 ) + 32 #prints debug info to console print sampleTime , "|" , "MST1:" , mst1 , "MST2:" , mst2 , "MST3:" , mst3 , "MST4:" , mst4 , "Pot1:" , pot1 , "LDR1:" , ldr1 , "TMP1:" , tmp1 #prints the debug info #adds the data to the mysql table cursor . execute ( "INSERT INTO piplanter_table_17(Time,mst1_V,mst2_V,mst3_V,mst4_V,pot1_V,ldr1_V,tmp1_F) VALUES(%s,%s,%s,%s,%s,%s,%s,%s)" , ( sampleTime , mst1 , mst2 , mst3 , mst4 , pot1 , ldr1 , tmp1 ) ) con . commit ( ) #this is important for live updating GPIO . output ( NPNtrans , False ) #turns the probes off #renders the image of the graph print "render start" os . system ( "php /opt/bitnami/apps/wordpress/htdocs/piplanter/renderScript.php" ) #renders the .png file print "render complete" #finds the newest image in the directory allfiles = sorted ( os . listdir ( '/opt/bitnami/apps/wordpress/htdocs/piplanter/renders/' ) , key = lambda p : os.path . getctime ( os.path . join ( '/opt/bitnami/apps/wordpress/htdocs/piplanter/renders/' , p ) ) ) newest = '/opt/bitnami/apps/wordpress/htdocs/piplanter/renders/' + allfiles [ - 1 ] print 'File for upload: ' + newest #prints location and file to console response = flickr . upload ( filename = newest , title = sampleTime , format = 'etree' ) #uploads the file to flickr photoID = response . find ( 'photoid' ) . text #gets the id of the photo for constructing a url print 'Upload Successful, Photo ID: ' + photoID #more debug info #tweets the image and data send = 'Brghtnss: ' + str ( format ( ( ( ( float ( ldr1 ) / 1024 ) * 100 ) ) , '.0f' ) ) + '% / ' + 'Tmprtr: ' + str ( format ( tmp1 , '.0f' ) ) + ' Dg F' + ' / Avg Plnt Moisture: ' + str ( format ( float ( ( float ( ( mst1 + mst2 + mst3 + mst4 ) / 4 ) / 1024 ) * 100 ) , '.0f' ) ) + '%' + ' Graph: ' + 'http://www.flickr.com/photos/97350286@N08/' + photoID + ' - www.esologic.com/?p=643' #builds the text of the tweet print "Tweeting:" , send #for debug purposes api . update_status ( send ) #tweets the tweet time . sleep ( . 1 ) GPIO . output ( sampleLED , False ) print "-----------end-----------" def water ( ) : print "===== Starting Watering Process =====" GPIO . output ( NPNtrans , True ) GPIO . output ( sampleLED , True ) time . sleep ( 1 ) sensor1_before = readadc ( 0 ) sensor2_before = readadc ( 1 ) sensor3_before = readadc ( 2 ) sensor4_before = readadc ( 3 ) before = "WATERING START / Moisture Before - " + "Sensor 1:" + str ( sensor1_before ) + " Sensor 2:" + str ( sensor2_before ) + " Sensor 3:" + str ( sensor3_before ) + " Sensor 4:" + str ( sensor4_before ) + " - Average:" + str ( ( float ( sensor1_before + sensor2_before + sensor3_before + sensor4_before ) / 4 ) ) api . update_status ( before ) print before GPIO . output ( pump , True ) time . sleep ( ontime ) GPIO . output ( pump , False ) time . sleep ( 60 ) #gives the water time to penetrate the soil sensor1_after = readadc ( 0 ) sensor2_after = readadc ( 1 ) sensor3_after = readadc ( 2 ) sensor4_after = readadc ( 3 ) after = "WATERING COMPLETED / Moisture After - " + "Sensor 1:" + str ( sensor1_after ) + " Sensor 2:" + str ( sensor2_after ) + " Sensor 3:" + str ( sensor3_after ) + " Sensor 4:" + str ( sensor4_after ) + " - Average: " + str ( ( float ( sensor1_after + sensor2_after + sensor3_after + sensor4_after ) / 4 ) ) api . update_status ( after ) print after GPIO . output ( NPNtrans , False ) GPIO . output ( sampleLED , False ) print "====== Watering Process Complete =====" #water() slowSample ( ) #runs the sample once before the interval starts, mostly a debug function scheduler = Scheduler ( standalone = True ) scheduler . add_interval_job ( slowSample , hours = 1 ) scheduler . start ( ) #runs the program indefianately once every hour

There you go! 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 in 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! (taken from)

MySQL Database

The database is extremely simple, after installing MySQL set it up and create table that follows this syntax:

CREATE TABLE piplanter_table_17(Sample_Number INT NOT NULL AUTO_INCREMENT PRIMARY KEY, Time VARCHAR(100), mst1_V VARCHAR(100), mst2_V VARCHAR(100), mst3_V VARCHAR(100), mst4_V VARCHAR(100), pot1_V VARCHAR(100), ldr1_V VARCHAR(100), tmp1_F VARCHAR(100) ); 1 CREATE TABLE piplanter_table_17 ( Sample_Number INT NOT NULL AUTO_INCREMENT PRIMARY KEY , Time VARCHAR ( 100 ) , mst1_V VARCHAR ( 100 ) , mst2_V VARCHAR ( 100 ) , mst3_V VARCHAR ( 100 ) , mst4_V VARCHAR ( 100 ) , pot1_V VARCHAR ( 100 ) , ldr1_V VARCHAR ( 100 ) , tmp1_F VARCHAR ( 100 ) ) ;

Pretty basic stuff, the table is just where the python script dumps the data every hour.

PChart Graph

The software driving the graphing part of the project is a bit of php graphing software called pchart. It allows me to graph mysql values from a table in a variety of ways. It is very important, and the code for the php script is as follows:

<?php /* Include all the classes */ include("/srv/www/lib/pChart/class/pData.class.php"); include("/srv/www/lib/pChart/class/pDraw.class.php"); include("/srv/www/lib/pChart/class/pImage.class.php"); $myData = new pData(); /* Create your dataset object */ $db = mysql_connect("localhost", "user", "pass"); //location of server, db username, db pass mysql_select_db("piplanter", $db); $Requete = "SELECT * FROM `piplanter_table_17`"; //table name $Result = mysql_query($Requete, $db); /*This fetches the data from the mysql database, and adds it to pchart as points*/ while($row = mysql_fetch_array($Result)) { $Time = $row["Time"]; $myData->addPoints($Time,"Time"); $mst1_V = $row["mst1_V"]; $myData->addPoints($mst1_V,"mst1_V"); $mst2_V = $row["mst2_V"]; $myData->addPoints($mst2_V,"mst2_V"); $mst3_V = $row["mst3_V"]; $myData->addPoints($mst3_V,"mst3_V"); $mst4_V = $row["mst4_V"]; $myData->addPoints($mst4_V,"mst4_V"); $ldr1_V = $row["ldr1_V"]; $myData->addPoints($ldr1_V,"ldr1_V"); $tmp1_F = $row["tmp1_F"]; $myData->addPoints($tmp1_F,"tmp1_F"); } $myData-> setSerieOnAxis("tmp1_F", 0); //assigns the data to the frist axis $myData-> setAxisName(0, "Degrees F"); //adds the label to the first axis $myData-> setSerieOnAxis("ldr1_V", 1); $myData-> setAxisName(1, "LDR"); $myData-> setSerieOnAxis("mst1_V", 2); $myData-> setSerieWeight("mst1_V",2); $myData-> setSerieOnAxis("mst2_V", 2); $myData-> setSerieOnAxis("mst3_V", 2); $myData-> setSerieOnAxis("mst4_V", 2); $myData-> setAxisName(2, "Relative Moisture"); $myData->setAbscissa("Time"); //sets the time data set as the x axis label $myData-> setSerieWeight("mst1_V",1); //draws the line tickness $myData->setPalette("mst1_V",array("R"=>58,"G"=>95,"B"=>205,"Alpha"=>80)); //sets the line color $myData-> setSerieWeight("mst2_V",1); $myData->setPalette("mst2_V",array("R"=>39,"G"=>64,"B"=>139,"Alpha"=>80)); $myData-> setSerieWeight("mst3_V",1); $myData->setPalette("mst3_V",array("R"=>0,"G"=>34,"B"=>102,"Alpha"=>80)); $myData-> setSerieWeight("mst4_V",1); $myData->setPalette("mst4_V",array("R"=>67,"G"=>110,"B"=>238,"Alpha"=>80)); $myData-> setSerieWeight("ldr1_V",2); $myData-> setSerieTicks("ldr1_V", 4); $myData-> setSerieWeight("tmp1_F",2); $myData-> setSerieTicks("tmp1_F", 4); $myPicture = new pImage(2000,500,$myData); /* Create a pChart object and associate your dataset */ $myPicture->setFontProperties(array("FontName"=>"/srv/www/lib/pChart/fonts/pf_arma_five.ttf","FontSize"=>6)); /* Choose a nice font */ $myPicture->setGraphArea(130,40,1900,300); /* Define the boundaries of the graph area */ $myPicture->drawScale(array("LabelRotation"=>320)); /* Draw the scale, keep everything automatic */ $Settings = array("R"=>250, "G"=>250, "B"=>250, "Dash"=>1, "DashR"=>0, "DashG"=>0, "DashB"=>0); /*The combination makes a cool looking graph*/ $myPicture->drawPlotChart(); $myPicture->drawLineChart(); $myPicture->drawLegend(30,320); //adds the legend //$date-> date("d-M-Y:H:i:s"); //$myPicture->autoOutput(); /* Build the PNG file and send it to the web browser */ $myPicture->render("/opt/bitnami/apps/wordpress/htdocs/piplanter/renders/".date("d-M-Y_H:i:s").".png"); ?> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 <?php /* Include all the classes */ include ( "/srv/www/lib/pChart/class/pData.class.php" ) ; include ( "/srv/www/lib/pChart/class/pDraw.class.php" ) ; include ( "/srv/www/lib/pChart/class/pImage.class.php" ) ; $myData = new pData ( ) ; /* Create your dataset object */ $db = mysql_connect ( "localhost" , "user" , "pass" ) ; //location of server, db username, db pass mysql_select_db ( "piplanter" , $db ) ; $Requete = "SELECT * FROM `piplanter_table_17`" ; //table name $Result = mysql_query ( $Requete , $db ) ; /*This fetches the data from the mysql database, and adds it to pchart as points*/ while ( $row = mysql_fetch_array ( $Result ) ) { $Time = $row [ "Time" ] ; $myData -> addPoints ( $Time , "Time" ) ; $mst1_V = $row [ "mst1_V" ] ; $myData -> addPoints ( $mst1_V , "mst1_V" ) ; $mst2_V = $row [ "mst2_V" ] ; $myData -> addPoints ( $mst2_V , "mst2_V" ) ; $mst3_V = $row [ "mst3_V" ] ; $myData -> addPoints ( $mst3_V , "mst3_V" ) ; $mst4_V = $row [ "mst4_V" ] ; $myData -> addPoints ( $mst4_V , "mst4_V" ) ; $ldr1_V = $row [ "ldr1_V" ] ; $myData -> addPoints ( $ldr1_V , "ldr1_V" ) ; $tmp1_F = $row [ "tmp1_F" ] ; $myData -> addPoints ( $tmp1_F , "tmp1_F" ) ; } $myData -> setSerieOnAxis ( "tmp1_F" , 0 ) ; //assigns the data to the frist axis $myData -> setAxisName ( 0 , "Degrees F" ) ; //adds the label to the first axis $myData -> setSerieOnAxis ( "ldr1_V" , 1 ) ; $myData -> setAxisName ( 1 , "LDR" ) ; $myData -> setSerieOnAxis ( "mst1_V" , 2 ) ; $myData -> setSerieWeight ( "mst1_V" , 2 ) ; $myData -> setSerieOnAxis ( "mst2_V" , 2 ) ; $myData -> setSerieOnAxis ( "mst3_V" , 2 ) ; $myData -> setSerieOnAxis ( "mst4_V" , 2 ) ; $myData -> setAxisName ( 2 , "Relative Moisture" ) ; $myData -> setAbscissa ( "Time" ) ; //sets the time data set as the x axis label $myData -> setSerieWeight ( "mst1_V" , 1 ) ; //draws the line tickness $myData -> setPalette ( "mst1_V" , array ( "R" = > 58 , "G" = > 95 , "B" = > 205 , "Alpha" = > 80 ) ) ; //sets the line color $myData -> setSerieWeight ( "mst2_V" , 1 ) ; $myData -> setPalette ( "mst2_V" , array ( "R" = > 39 , "G" = > 64 , "B" = > 139 , "Alpha" = > 80 ) ) ; $myData -> setSerieWeight ( "mst3_V" , 1 ) ; $myData -> setPalette ( "mst3_V" , array ( "R" = > 0 , "G" = > 34 , "B" = > 102 , "Alpha" = > 80 ) ) ; $myData -> setSerieWeight ( "mst4_V" , 1 ) ; $myData -> setPalette ( "mst4_V" , array ( "R" = > 67 , "G" = > 110 , "B" = > 238 , "Alpha" = > 80 ) ) ; $myData -> setSerieWeight ( "ldr1_V" , 2 ) ; $myData -> setSerieTicks ( "ldr1_V" , 4 ) ; $myData -> setSerieWeight ( "tmp1_F" , 2 ) ; $myData -> setSerieTicks ( "tmp1_F" , 4 ) ; $myPicture = new pImage ( 2000 , 500 , $myData ) ; /* Create a pChart object and associate your dataset */ $myPicture -> setFontProperties ( array ( "FontName" = > "/srv/www/lib/pChart/fonts/pf_arma_five.ttf" , "FontSize" = > 6 ) ) ; /* Choose a nice font */ $myPicture -> setGraphArea ( 130 , 40 , 1900 , 300 ) ; /* Define the boundaries of the graph area */ $myPicture -> drawScale ( array ( "LabelRotation" = > 320 ) ) ; /* Draw the scale, keep everything automatic */ $Settings = array ( "R" = > 250 , "G" = > 250 , "B" = > 250 , "Dash" = > 1 , "DashR" = > 0 , "DashG" = > 0 , "DashB" = > 0 ) ; /*The combination makes a cool looking graph*/ $myPicture -> drawPlotChart ( ) ; $myPicture -> drawLineChart ( ) ; $myPicture -> drawLegend ( 30 , 320 ) ; //adds the legend //$date-> date("d-M-Y:H:i:s"); //$myPicture->autoOutput(); /* Build the PNG file and send it to the web browser */ $myPicture -> render ( "/opt/bitnami/apps/wordpress/htdocs/piplanter/renders/" . date ( "d-M-Y_H:i:s" ) . ".png" ) ; ?>

As you may be able to guess, upon the calling of this script, the program looks for a table called “piplanter_table_17” and does a bunch of stuff as commented to produce a graph. This is what a sample graph looks like:

This is data taken over 6 days, and it’s a lot to look at, but it’s good stuff.

Twitter & Flickr Integration

As you hopefully derived from the python code, this project uses Twitter to send data to me. Instead of using an email server or sending sms messages, I decided on twitter because of a few reasons. I use the service constantly, so I won’t ever miss a tweet. The API seemed really easy to use (and it was!) and allowed more than one person to acess the data at any one time. I decided to use flickr as my image hosting service for a lot of the same reasons, but the main one was their 1TB storage per person. You’ve already seen a sample flickr upload, so here’s a sample tweet:

That’s essentially it! Thank you for reading, and please ask questions.