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)

The different classes of analytics

Analytics can be applied for different purposes and using different techniques. They are generally separated into three different families: descriptive, predictive, and prognostic. These are ordered from the simplest to the most advanced.

Descriptive analytics

Descriptive analytics are the most basic class of analytics. They analyze past data to try and provide a broad view of the fleet. In other words, descriptive analytics tries to answer the question What happened? These analytics use data mining, aggregation, or visual intelligence techniques to understand the status of the assets. In the I-IoT, the most common technique used for descriptive analytics is KPI monitoring.

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