Analyzing Live Data Streams In Cloud Using Raspberry Pi, DHT11, And ThingSpeak

Introduction

 

In this IoT article, we will use a DHT11, Raspberry Pi, and ThingSpeak to analyze the temperature and humidity.

 

Requirement

• DHT11 - Temperature and Humidity Sensor Module
• ThingSpeak
• Raspberry Pi
• Putty

DHT11 Sensor Actions

 

Refer to my previous article Stream Sensor Data In Real-Time With IoT Hub Using PowerBI

 

Thingspeak 

 

ThingSpeak allows you to aggregate, visualize, and analyze live data streams in the cloud. ThingSpeak provides instant visualizations of data posted by your devices or equipment. Execute MATLAB code in ThingSpeak, and perform online analysis and processing of the data as it comes in. ThingSpeak accelerates the development of proof-of-concept IoT systems, especially those that require analytics. You can build IoT systems without setting up servers or developing web software.

 

Step 1

• Set up the DHT11 humidity sensor on the Raspberry Pi.
• GPIO pin is 27.

  

 

Download the Adafruit DHT11 library. In the terminal, type the following command.

git clone https://github.com/adafruit/Adafruit_Python_DHT.git

Navigate to Adafruit_Python_DHT directory (folder).

cd Adafruit_Python_DHT

Run the following commands in the terminal. 

sudo apt-get install build-essential python-dev  # python2
sudo apt-get install build-essential python3-dev  # python3

To install the library, in the terminal, type the following.

sudo python setup.py install  # python2
sudo python3 setup.py install  # python3

Navigate to the example folder.

cd examples
sudo nano dhtsimple.p

Replace the following demo code.

import Adafruit_DHT  # is a must
while True:
    humidity, temperature = Adafruit_DHT.read_retry(11, 27)  # GPIO27 (BCM notation)
    print ("Humidity = {} %; Temperature = {} C".format(humidity, temperature))

Run the program.

sudo python dhtsimple.py

Output 

 

 

 

Step 2

• Open Thingspeak (https://thingspeak.com).
• Create a new channel and select fields 1 and 2.

• Select Ras_Pi channel and API Keys.

• Get the Write API Key or generate the new Write API Key.

 

Step 3

 

Open the new Python file and name it as dht1234567.py like below.

sudo nano dht1234567.py

Replace the following code.

import httplib, urllib
import time
import Adafruit_DHT
sleep = 30 # how many seconds to sleep between posts to the channel
key = '****************'  # Write API key

humidity, temperature = Adafruit_DHT.read_retry(11, 27)  # GPIO27 (BCM notation)


#Report Raspberry Pi internal temperature to Thingspeak Channel
def thermometer():
    while True:
        headers = {"Content-typZZe": "application/x-www-form-urlencoded","Accept": "text/plain"}
        conn = httplib.HTTPConnection("api.thingspeak.com:80")
        try:
            params = urllib.urlencode({'field1': temperature, 'key':key }) # channel name is field1 or field 2
            conn.request("POST", "/update", params, headers)
            response = conn.getresponse()
            print humidity
        print temperature
            #print response.status, response.reason
            data = response.read()
            conn.close()
        except:
            print "connection failed"
        break
#sleep for desired amount of time
if __name__ == "__main__":
        while True:
                thermometer()
                time.sleep(sleep)

Run the program.

sudo python dht1234567.py

 

Graphical representation.

 

 

 

Download all of this Channel's feeds in the CSV format.

 

Summary

 

Finally, we have successfully created a graph that live-streams the data in the cloud with Raspberry Pi and ThingSpeak.