Book Image

Mastering IOT

By : Colin Dow, Perry Lea
Book Image

Mastering IOT

By: Colin Dow, Perry Lea

Overview of this book

The Internet of Things (IoT) is the fastest growing technology market. Industries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. We’ll begin our journey with an introduction to Raspberry Pi and quickly jump right into Python programming. We’ll learn all concepts through multiple projects, and then reinforce our learnings by creating an IoT robot car. We’ll examine modern sensor systems and focus on what their power and functionality can bring to our system. We’ll also gain insight into cloud and fog architectures, including the OpenFog standards. The Learning Path will conclude by discussing three forms of prevalent attacks and ways to improve the security of our IoT infrastructure. By the end of this Learning Path, we will have traversed the entire spectrum of technologies needed to build a successful IoT system, and will have the confidence to build, secure, and monitor our IoT infrastructure. This Learning Path includes content from the following Packt products: Internet of Things Programming Projects by Colin Dow Internet of Things for Architects by Perry Lea
Table of Contents (34 chapters)
Title Page
Copyright
About Packt
Contributors
Preface
Free Chapter
1
The IoT Story
Index

Writing a simple Python program


We will write a simple Python program that contains a class. To facilitate this, we will use Thonny, a Python IDE that comes pre-installed with Raspbian and has excellent debug and variable introspection functionalities. You will find that its ease of use makes it ideal for the development of our projects.

Creating the class

We will begin our program by creating a class. A class may be seen as a template for creating objects. A class contains methods and variables. To create a class in Python with Thonny, do the following:

  1. Load Thonny through Application Menu | Programming | Thonny. Select New from the top left and type the following code:
class CurrentWeather:
weather_data={'Toronto':['13','partly sunny','8 km/h NW'],
'Montreal':['16','mostly sunny','22 km/h W'],
                'Vancouver':['18','thunder showers','10 km/h NE'],
                'New York':['17','mostly cloudy','5 km/h SE'],
                'Los Angeles':['28','sunny','4 km/h SW'],
          ...