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)

Understanding the role of the infrastructure

In this book, in Developing our batch analytics with Airflow section in Chapter 8, Implementing a Custom Industrial IoT Platform, in AWS IoT Analytics section Chapter 10, Implementing a Cloud Industrial IoT Solution with AWS, in Dataflow section in Chapter 11, Implementing a Cloud Industrial IoT Solution with Google Cloud, and in Azure analytics section in Chapter 12, Performing a Practical Industrial IoT Solution with Azure, we discovered how to build analytics based on the cloud or, generally speaking, a centralized infrastructure. We also learned about cold paths and hot paths. From a theoretical point of view, the implementation of analytics should be agnostic with regard to where they are deployed and how we push data. Unfortunately, this is not always the case.

Analytics are strictly coupled with the support they want from the...