Book Image

Industrial Internet Application Development

By : Alena Traukina, Jayant Thomas, Prashant Tyagi, Veera Kishore Reddipalli
Book Image

Industrial Internet Application Development

By: Alena Traukina, Jayant Thomas, Prashant Tyagi, Veera Kishore Reddipalli

Overview of this book

The Industrial Internet refers to the integration of complex physical machines with networked sensors and software. The growth in the number of sensors used in industrial machinery has led to an exponential increase in data being captured for predictive analytics. Industrial Internet Application Development is a practical guide for developers who want to create applications that leverage the full capabilities of IIoT. You will get started by learning how to develop your first IIoT application and understanding its deployment and security. Once you’re familiar with what IIoT is, you will move on to exploring Edge Development along with the analytics aspect of the IIoT stack. In later chapters, you’ll get to grips with the deployment of IIoT applications on the Predix platform. As you cover these concepts, you’ll be able to identify key elements of the development framework and understand their importance while considering architecture and design for IIoT applications. By the end of this book, you will have the skills you need to deploy IIoT applications on the Predix platform and incorporate best practices for developing fault-tolerant and reliable IIoT systems.
Table of Contents (13 chapters)
Free Chapter
1
IIoT Fundamentals and Components
11
Future Direction of the IIoT

Advanced Analytics for the IIoT

In this chapter, we will cover the concepts of advanced analytics and how it helps in IIoT use cases to provide insights, and to efficiently run manufacturing process and control systems for better productivity. Analytics that come under the category of complex data analysis, using techniques such as machine learning, are referred to in this chapter as advanced analytics. By the end of this chapter, you will have learned some of the IIoT business use cases and how machine learning techniques help in solving them. From the technical side, we will cover machine learning concepts at a high level, and frameworks such as Apache Spark ML and TensorFlow, as well as other tooling that is available to us.

In this chapter, we will cover the following topics:

  • IIoT business use cases and analytics
  • IIoT analytics classification—reliable, efficient, and...