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

IIoT analytics – cloud and edge

Based on the IIoT use cases, the analytics need to be executed on the edge device closer to the controller so that it can react using a standard operation procedure based on the mission -critical events. On the other hand, there are analytics that typically run for a longer time and need to process large amount of datasets, which is at a fleet level. Such analytics fall under big data analytics and require high computing power to distribute the data computation generally preferred to run in a cloud environment for scalability and cost reasons. In this section, we will discuss both the cloud-based and edge-based analytics and technologies that can be used.

Cloud-based analytics

As mentioned...