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)

Open System Architecture (OSA)

The OSA summarizes the concepts we discussed previously in a single picture. In the Prescriptive analytics section, we highlighted how CBM is one of the most valuable aspects of I-IoT analytics and how it can support insights from descriptive analytics all the way through to prescriptive analytics. The OSA for CBM is depicted as follows:

The OSA model applied to the I-IoT

The OSA for CBM is the most popular framework. It consists of six layers—Data Acquisition, Signal Processing, Condition Monitoring, Health Assessment, Prognostics, and Decision Support. All of these steps can be implemented in a cloud-based architecture and partially on-premises, as explained in the previous sections. In particular, signal processing and condition monitoring can be implemented by using on-stream analytics or, generally speaking, rule-based engines. The health...