Real Time Temperature Plotting with Raspberry Pi and Plot.ly

1. Raspberry Pi3
2. Connecting pins
3. 1KΩresistor (17 pieces)
4. 10K pot
5. 0.1µF capacitor
6. 100µF capacitor
7. ADC0804 IC
8. LM35 Temperature Sensor
9. Bread Board

FULL CIRCUIT:

ADC0804 Pin-out:

LM35 – Pin Out:

ADC0804 and Pi3 Connections
S.NO	PI3	ADC0804
1	Pin02 - +5V	Pin20 –VCC
2	Pin06 – GND	Pin 1 –CS Pin 2- RD Pin 8 – AGND Pin 9 – DGND Pin 4 – CLKIN via 0.1uF Pin 19 – CLKR via 1k resistor and 0.1uF respectively Pin07 – V-
3	Pin07 – GPIO4	Pin 18 – DB0 via Voltage Divider
4	Pin11 – GPIO 17	Pin 18 – DB0 via Voltage Divider
5	Pin13 – GPIO27	Pin 18 – DB0 via Voltage Divider
6	Pin15 – GPIO22	Pin 18 – DB0 via Voltage Divider
7	Pin29 – GPIO5	Pin 18 – DB0 via Voltage Divider
8	Pin31 – GPIO6	Pin 18 – DB0 via Voltage Divider
9	Pin33 – GPIO13	Pin 18 – DB0 via Voltage Divider
10	Pin35 –GPIO 19	Pin 18 – DB0 via Voltage Divider
11	-	Pin 3 WR to Pin 5 INTR
LM35 Connections:
S.NO	LM35 Pin	CONNECTION
1	Pin01 – VCC	Pin02 of Pi3 - +5V
2	Pin02 – SIGNAL	PIN06 of ADC0804 – V+ PIN06 of PI3 – GND via 100uF
3	Pin03 – GND	PIN 06 of PI3 – GND
Potentiometer Connections:
S.NO	Potentiometer Pin	CONNECTION
1	Pin01 – VCC	Pin02 of Pi3 - +5V
2	Pin02 – SIGNAL – SET To 1V by Multimeter	PIN09 of ADC0804 – Vref/2
3	Pin03 – GND	PIN 06 of PI3 – GND
Circuit

• Step 1:
Go to www.plot.ly and create a new plotly account. After that go to https://plot.ly/settings/api and create atleast two new streaming tokens. Make a note of your username, API key, streaming tokens.
• Step 2:
Next, install the required modules and dependencies (you can copy and paste this in your terminal):

sudo apt-get install python-dev
wget https://bitbucket.org/pypa/setuptools/raw/bootstrap/ez_setup.py -O - | sudo python
sudo easy_install -U distribute
sudo apt-get install python-pip
sudo pip install rpi.gpio
sudo pip install plotly

• Step 3:
Create a new folder for your project. Create a config.json file in the said folder using a text editor and input your plotly API key, and your plotly streaming tokens.

Example config.json content:
{
"plotly_streaming_tokens": ["your_stream_token", "another_stream_token"],
"plotly_api_key": "abcdefghij",
"plotly_username": "ABCDEFGH"
}
Now Create a tmp.py file in the same folder to read temperature values and integrate them to plotly.

import plotly.plotly as py
import json
import time
import datetime
import RPi.GPIO as IO            # calling for header file which helps us use GPIO’s of PI
import sys
IO.setwarnings(False)            # do not show any warnings

with open('./config.json') as config_file:
    plotly_user_config = json.load(config_file)

py.sign_in(plotly_user_config["plotly_username"], plotly_user_config["plotly_api_key"])

url = py.plot([
    {
        'x': [], 'y': [], 'type': 'scatter',
        'stream': {
            'token': plotly_user_config['plotly_streaming_tokens'][0],
            'maxpoints': 200
        }
    }], filename='Raspberry Pi Streaming Example Values')

print "View your streaming graph here: ", url

stream = py.Stream(plotly_user_config['plotly_streaming_tokens'][0])
stream.open()

#the main sensor reading and plotting loop

x=1
b0 =0                                       # integer for storing the delay multiple
b1 =0
b2 =0
b3 =0
b4 =0
b5 =0
b6 =0
b7 =0
IO.setmode (IO.BCM)                # programming the GPIO by BCM pin numbers. (like PIN29 as‘GPIO5’)
IO.setup(4,IO.IN)                        # initialize GPIO Pins as input
IO.setup(17,IO.IN)
IO.setup(27,IO.IN)
IO.setup(22,IO.IN)
IO.setup(5,IO.IN)
IO.setup(6,IO.IN)
IO.setup(13,IO.IN)
IO.setup(19,IO.IN)
while 1:                                              # execute loop forever
    if (IO.input(19) == True):
        time.sleep(0.001)
        if (IO.input(19) == True):
            b7=1                                     # if pin19 is high bit7 is true
    if (IO.input(13) == True):
        time.sleep(0.001)
        if (IO.input(13) == True):
            b6=1                                     # if pin13 is high bit6 is true
    if (IO.input(6) == True):
        time.sleep(0.001)
        if (IO.input(6) == True):
            b5=1                                    # if pin6 is high bit5 is true
    if (IO.input(5) == True):
        time.sleep(0.001)
        if (IO.input(5) == True):
            b4=1                                   # if pin5 is high bit4 is true           
    if (IO.input(22) == True):
        time.sleep(0.001)
        if (IO.input(22) == True):
            b3=1                                  # if pin22 is high bit3 is true
    if (IO.input(27) == True):
        time.sleep(0.001)
        if (IO.input(27) == True):
            b2=1                                 # if pin27 is high bit2 is true            
    if (IO.input(17) == True):
        time.sleep(0.001)
        if (IO.input(17) == True):
            b1=1                                  # if pin17 is high bit1 is true
    if (IO.input(4) == True):
        time.sleep(0.001)
        if (IO.input(4) == True):
            b0=1                                      # if pin4 is high bit0 is true
  
    x = (1*b0)+(2*b1)                        # representing the bit values from LSB to MSB
    x = x+(4*b2)+(8*b3)
    x = x+(16*b4)+(32*b5)
    x = x+(64*b6)+(128*b7)
    x = x/1.275
    temp_C = x
    # convert celsius to fahrenheit
    temp_F = (x * 9.0 / 5.0) + 32
    # remove decimal point from millivolts
    # show only one decimal place for temprature and voltage readings
    temp_C = "%.1f" % temp_C
    temp_F = "%.1f" % temp_F

    
    #print the ADC value
    print(temp_C)
    # write the data to plotly
    stream.write({'x': datetime.datetime.now(), 'y': temp_C})

    # delay between stream posts
    time.sleep(0.50)


    #temp=100,ref=2000mv,read=255/200=1.275countper10mv or 1.275count for 1degree

                                         
    b0=b1=b2=b3=b4=b5=b6=b7=0      # reset the values
    time.sleep(0.50)          

Run the python code in shell and visit www.plot.ly/~yourusername/0/ to see your data being plotted live. In case of above example, the URL to check would be www.plot.ly/~Karth195/0/
Vary the temperature detected by LM35 sensor by holding a match or lighter to it and see the sensor values on your Pi-3 screen as well as the data being plotted on plotly!