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


In this chapter, we looked into how the S95 standard addresses asset modeling and exchange of asset data between different levels of an enterprise control system. Then, we overviewed the existing database management systems (including blockchain) with a focus on the data types they can store. Furthermore, we compared the most widely used time series storage.

We provided a detailed instruction and a sample code to build a Node.js application that simulates reading of time series measurements. Touching upon different types of analytics, we highlighted the analytical functions of the InfluxDB database. Then, we demonstrated how to enable descriptive analytics with InfluxDB for the Node.js app we had previously built. In addition, we showed how to set up time series visualizations with Highcharts and Grafana and to configure email and Slack notifications and alerts from Grafana...