Book Image

Hands-On Industrial Internet of Things

By : Giacomo Veneri, Antonio Capasso
Book Image

Hands-On Industrial Internet of Things

By: Giacomo Veneri, Antonio Capasso

Overview of this book

We live in an era where advanced automation is used to achieve accurate results. To set up an automation environment, you need to first configure a network that can be accessed anywhere and by any device. This book is a practical guide that helps you discover the technologies and use cases for Industrial Internet of Things (IIOT). Hands-On Industrial Internet of Things takes you through the implementation of industrial processes and specialized control devices and protocols. You’ll study the process of identifying and connecting to different industrial data sources gathered from different sensors. Furthermore, you’ll be able to connect these sensors to cloud network, such as AWS IoT, Azure IoT, Google IoT, and OEM IoT platforms, and extract data from the cloud to your devices. As you progress through the chapters, you’ll gain hands-on experience in using open source Node-Red, Kafka, Cassandra, and Python. You will also learn how to develop streaming and batch-based Machine Learning algorithms. By the end of this book, you will have mastered the features of Industry 4.0 and be able to build stronger, faster, and more reliable IoT infrastructure in your Industry.
Table of Contents (18 chapters)

Deploying Analytics on an IoT Platform

In the previous chapters, we looked at the differences between different types of analytics. We implemented some examples of prognostic and diagnostic analytics in the world of the I-IoT. We also studied how to deploy our analytics on the most common platforms and how to use open source technologies.

In this chapter, we will finalize our exercise by delivering the algorithms developed in Chapter 14, Implementing a Digital Twin – Advanced Analytics. In particular, we want to highlight the major differences between three platforms: AWS, Azure, and GCP. We will discover that all three platforms adopt the same principles of providing a computational infrastructure for training and a service-oriented platform for using the analytical model.

In this chapter, we will explore the following topics:

  • Deploying diagnostic analytics using the...