Python in IoT(Internet of Things)

Python programming powers intuitive interfaces of intelligent and effective Internet of Things (IoT) systems that are paramount in remote sensor networks, big data and data analysis, automation, and machine learning. IoT applications function efficiently with the help of Python libraries/packages which include:

Numpy

Numpy is a scientific computing package that helps to create datasets to test with the time series data in IoT.  Numpy features are used in IoT to read sensor bulk data from the database inbuilt functions in the system

Sockets and MySQLdb

Sockets that facilitate networking in IoT devices include TCP/IP and UDP, which are compatible to work with Python packages. TCP/IP and UDP act as transport layer protocols for communication. The MySQLdb is a go-to relational format database that helps in the development of remote stores for the IoT system.

Matplotlib

To get data insights, matplotlib visualizes the most paramount operations by giving a variety of graphs to represent the data.

Requests, Tkinter and Tensorflow

To make HTTP calls and parse responses in Python, the request package acts as a major protocol for data exchanges. Tkinter GUI puts the aspects of Python script in a controlled distribution, which enables functional testing and repeated executions in IoT Python devices. Therefore, the numerical computations of machine learning initiated into the IoT systems utilize the representation in data flow graphs dealing with huge non-linear datasets and deep learning aspects.

IoT devices used to develop applications in IoT

• Raspberry Pi Model 3

• Intel Edison

• Arduino

IoT sensors simulators used in Python programming include:

MQ Telemetry Transport (MQTT) sensor simulator

MQTT protocol for the IoT in Python enables high-speed data exchange with low payload communication between the devices. User-friendly requests of MQTT are made directly in Python. Data is collected in real-time and easily analyzed in mathematical computation libraries like matplotlib. The diagram below shows the steps used for the data flow:

Data logging using MQTT (install using pip install paho-mqtt) Python is displayed below:

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import paho.mqtt.client as mqtt
#Callback
for received data from server
def on_connect(data_iot, user, events):
  print(“connected with code” + str(events))
data = mqtt.Client()
Data.on_connect = on_connect
Data.on_message = on_message
data.loop_forever()

For instance, the MQTT protocol is used to send data of a light bulb and install required dependencies and libraries as indicated below:

Azure IoT SDK in Python

Azure IoT hub offers a variety of features for IoT SDK usage which provides the ability to connect devices and services. The IoT SDK is supported by the MQTT protocol which facilitates the data exchange processes. The device requirements to be used along with Python include:

• Python version 3.7+: helps in both asynchronous and synchronous API

• Azure-iot-device library

The IoT hub SDK helps with the following aspects: access, processing, and analysis of data for machine learning applications.
The Azure IoT hub helps collect messages and feedback data collected by IoT devices and is displayed in the code below:

Countly IoT Raspberry Pi SDK

Sending data and visualizing data on a dashboard is simplified by involving the Countly IoT Pi SDK, which relies on internet connectivity for efficient and effective data insights from the device.
The code below is used to start the process of collecting data using Countly IoT Pi SDK in Python. Install by running: pip install Raspberry_SDK:

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from Raspberry_SDK.Countly
import Countly
#intiate the SDK
Countly = Countly(“SERVER_URL”, “APP_KEY”, 0)
#Send an event
countly.event(“NAME”, VALUE)

Countly SDK also helps to retrieve data events for both analog and digital circuits. Use case of Countly IoT Raspberry Pi SDK is applicable in temperature room measuring and Bulb light. For instance, the server gets to pass the application key to collect the data and data is being manipulated by GroveAPI for raspberry IoT as displayed below: