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)

QuickSight

QuickSight mainly relates to business intelligence capabilities, but also offers an easy way of IoT data visualization. Although QuickSight is not exactly related to IoT, it has great connectivity with AWS IoT Analytics and allows you to develop a user interface with just a few clicks:

  1. From the AWS console, click on the QuickSight option.
  2. The first time you click on QuickSight, it will ask you to register. Choose the free account.
  1. To enable the data source, check the box next to the Amazon IoT Analytics checkbox, as shown in the following screenshot:
Configuring QuickSight
  1. Finally, from the data set, create a new instance IoT Analytics and select our previously created dataset signals_dataset:
Creating a new AWS IoT Analytics datasource

Now, drag and drop our signal (in this case the temperature) into the autograph space:

Visualizing data with QuickSight
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