Industrial Internet Application Development

Simplify IIoT development using the elasticity of Public Cloud and Native Cloud Services

Alena Traukina, Jayant Thomas, Prashant Tyagi, Kishore Reddipalli

• Publisher: Packt Publishing
• Year: 2018
• ISBN:
  9781788297585
• Edition: 1
• Topic: Informatica
• Subtopic: Sviluppo di applicazioni

Your one-stop guide to designing, building, managing, and operating Industrial Internet of Things (IIoT) applications

Key Features

• Build IIoT applications and deploy them on Platform as a Service (PaaS)
• Learn data analytics techniques in IIoT using Spark and TensorFlow
• Understand and combine Predix services to accelerate your development

Book Description

The Industrial Internet refers to the integration of complex physical machines with networked sensors and software. The current growth in the number of sensors deployed in heavy machinery and industrial equipment will lead to an exponential increase in data being captured that needs to be analyzed for predictive analytics. This also opens up a new avenue for developers who want to build exciting industrial applications.

Industrial Internet Application Development serves as a one-stop guide for software professionals wanting to design, build, manage, and operate IIoT applications. You will develop your first IIoT application and understand its deployment and security considerations, followed by running through the deployment of IIoT applications on the Predix platform. Once you have got to grips with what IIoT is, you will move on to exploring Edge Development along with the analytics portions of the IIoT stack. All this will help you identify key elements of the development framework, and understand their importance when considering the overall architecture and design considerations for IIoT applications. By the end of this book, you will have grasped how to deploy IIoT applications on the Predix platform, as well as incorporate best practices for making fault-tolerant and reliable IIoT systems.

What you will learn

• Connect prototype devices to CloudStore data in IIoT applications
• Explore data management techniques and implementation
• Study IIoT applications analytics using Spark ML and TensorFlow
• Deploy analytics and visualize the outcomes as Alerts
• Understand continuous deployment using Docker and Cloud Foundry
• Make your applications fault-tolerant and monitor them with New Relic
• Understand IIoT platform architecture and implement IIoT applications on the platform

Who this book is for

This book is intended for software developers, architects, product managers, and executives keen to gain insights into Industrial Internet development. A basic knowledge of any popular programming language such as Python will be helpful.

Implementing IIoT Applications with Predix

In this chapter, you will learn in more detail about the components and capabilities of the Asset, Time Series, and Analytics Framework services from GE's Predix catalog. In particular, we will demonstrate how to create instances of the services, bind them with your apps, and configure client authentications. You will also learn how to use various HTTP requests in Postman to query and manage assets, and how to build and deploy apps to read and analyze time series data. Furthermore, we will provide detailed instructions on how to enable advanced visualization with components of GE's Predix UI Framework.

This chapter covers the following topics:

• Using the Asset service for asset modeling
• Creating an instance of the Asset service and binding it to your app
• Configuring client authentications for managing assets via the Asset service
• Adding assets to the Asset service
• Changing assets
• Viewing, deleting, and querying assets
• Additional capabilities of the Asset service
• Building an app to read time series data
• Creating an instance of the Time Series service
• Binding an instance of the Times Series service to your app
• Validating ingestions of time series data
• Components and capabilities of the Analytics Framework service
• Creating an instance of the Analytics Framework service and binding it to your app
• Building an analytical app to work with the Analytics Framework service

• Adding an analytical app to the Analytics Catalog of the Analytics Framework service
• Validating, testing, and deploying an analytical app
• Executing an analytical application
• Enabling data visualizations with GE's Predix UI Framework

Basics of asset modeling with the Asset service

This section overviews GE's Predix's Asset service, looking into how it can help to model assets. We will also provide two examples, illustrating how asset models describe objects in the JSON format.

The Asset service in detail

The Asset service by GE's Predix is designed to assist developers in creating, storing, and updating data for asset models, while enabling consumers to retrieve it.

An asset model consists of domain objects (for instance, classifications and assets) described in JSON. The objects are actually random sets of name-value pairs with a unique Uniform Resource Identifier (URI), indicating an appropriate asset instance stored in a graph database.

In the next subsection, we will provide an example of a classification object (Countries) to illustrate its JSON representation in an asset model.

An example of a classification object

The following figure is a graphical representation of a simple classification object consisting of two components:

A hierarchy of the Countries classification object

In the JSON format, the Countries classification object will be represented this way:

[
 {
 "uri": "/countries",
 "name": "Countries",
 "obsolete": false,
 "attributes": {
 }
 },
 {
 "uri": "/countries/USA",
 "name": "USA",
 "parent": "/countries",
 "obsolete": false,
 "attributes": {
 }
 },
 {
 "uri": "/countries/Japan",
 "name": "Japan",
 "parent": "/countries",
 "obsolete": false,
 "attributes": {
 }
 }
]

You can find this and more examples, as well as additional information about the Asset service in GE's Predix documentation: https://docs.predix.io/en-US/content/service/data_management/asset/.

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