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
IIoT Fundamentals and Components
Future Direction of the IIoT

Understanding the analytics

Big data analytics aims at revealing patterns, correlations, and providing other valuable insights based on processing of large data quantities. By capturing and analyzing big data—large and varied datasets—businesses can better understand their workflows, customer behavior, market trends, growth opportunities, and so on.

Previously, to take an informed decision, a company would have to first gather data, then analyze it, and integrate it into the decision-making process. The whole cycle could take quite a long time to complete. With big data analytics, businesses can speed it up, which gives them the competitive advantage of being more agile.

It is possible to distinguish the following four types of analytics:

  • Descriptive analytics: It helps you to get a historical overview of events over a given period and prepare the resultant data...