Book Image

Enterprise Internet of Things Handbook

By : Arvind Ravulavaru
Book Image

Enterprise Internet of Things Handbook

By: Arvind Ravulavaru

Overview of this book

There is a lot of work that is being done in the IoT domain and according to Forbes the global IoT market will grow from $157B in 2016 to $457B by 2020. This is an amazing market both in terms technology advancement as well as money. In this book, we will be covering five popular IoT platforms, namely, AWS IoT, Microsoft Azure IoT, Google IoT Core, IBM Watson IoT, and Kaa IoT middleware. You are going to build solutions that will use a Raspberry Pi 3, a DHT11 Temperature and humidity sensor, and a dashboard to visualize the sensor data in real-time. Furthermore, you will also explore various components of each of the platforms that are needed to achieve the desired solution. Besides building solutions, you will look at how Machine Learning and IoT go hand in hand and later design a simple predictive web service based on this concept. By the end of this book, you will be in a position to implement an IoT strategy best-fit for your organization
Table of Contents (12 chapters)

IoT and Machine Learning

In the last five chapters, we have learned how to work with five different IoT platforms, performing the simple operation of sending data from our smart device to the platform, as well as the means to build visualization.

In this chapter, we are going to take this process one level forward by adding intelligence to the solution that we are building.

We are going to use Azure Machine Learning (AML) Studio to build a machine learning (ML) model from existing weather data, and from this data model, we are going to make a prediction as to whether it will rain using temperature and humidity as an input.

The topics covered in this chapter are as follows:

  • What is machine learning?
  • What is AML and how do we use it?
  • Building and validating the AML model using web services.