This is the code repository for Industrial Internet Application Development, published by Packt.
Simplify IIoT development using the elasticity of Public Cloud and Native Cloud Services
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.
This book covers the following exciting features: 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
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02. The code files for chapters are placed in their respective folders. Chapters 1, 5, 7, and 11 do not have code files. Codes of chapters 4 and 10 are present in the book itself.
The code will look like the following:
network={
ssid="YOUR_SSID"
psk="YOUR_WIFI_PASSWORD"
}
Following is what you need for this book: 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.
With the following software and hardware list you can run all code files present in the book (Chapter 1-11).
| Chapter | Software required | OS required |
|---|---|---|
| 3, 6 | Node.js 6+ | Windows, Mac OS X, and Linux (Any) |
| 3, 6 | Docker | Windows, Mac OS X, and Linux (Any) |
| 3 | PostgreSQL | Windows, Mac OS X, and Linux (Any) |
| 3 | The Cloud Foundry CLI | Windows, Mac OS X, and Linux (Any) |
| 3 | Modbus | Windows, Mac OS X, and Linux (Any) |
| 3 | NodeOPCUA | Windows, Mac OS X, and Linux (Any) |
| 3 | RPIO | Windows, Mac OS X, and Linux (Any) |
| 3 | WebSocket | Windows, Mac OS X, and Linux (Any) |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Alena Traukina is the IoT practice lead at Altoros. She has over 12 year experience in the delivery and support of business-critical software applications, working closely with business owners and providing strategic and organizational leadership for software development. Over the years, Alena has served in different capacities, ranging from software engineer, to software engineering manager, to head of Altoros's Ruby department. She was also one of the first GE Predix Influencers.
Jayant Thomas (JT) has a passion for IoT, machine learning, and cloud-native architectures at scale. His passion has led him to many successful adventures at Veritas, GE, Oracle, AT&T, Nuance, and other start-ups, building platforms at scale. JT is an MBA graduate from UC Davis, and has an M.Tech from NIIT, as well as more than 15 patents in IoT, NLP processing, and cloud architectures. JT is also an enthusiastic speaker/writer, and has contributed to many conferences and meetups. In addition, JT is an active fitness and health freak, dabbling in various diets and health fads.
Prashant Tyagi is responsible for enabling the big data strategy at GE Digital for IIoT, leveraging IT and operational data for predictive analytics. He works with P&L verticals to enable their IoT use cases on the data and analytics platform. He is on the board of ISSIP, focused on service innovation. He leads a cross-industry special interest group on IoT and analytics, and is an adviser to the open source fog computing initiative, ioFog, which is an Eclipse foundation initiative. He holds a B.Tech from IIT Delhi, an MBA from IIM Bangalore, and an MS in computer science from Clemson University. He has publications in leading journals and magazines and is a renowned public speaker and panelist, having featured at several conferences.
Kishore Reddipalli is a software technical director and expert in building IIoT big data and cloud computing platforms and products at ultra scale. He is passionate about building software for analytics and machine learning to make the authoring of algorithms at scale, from inception to production, a simpler process. He has been a speaker at global conferences on big data technologies. Over the years, he has provided leadership in various capacities. Throughout his career, his roles have ranged from software engineer to director of engineering and architecture for the development of platforms and products in domains such as clinical decision support systems, electronic medical records, Predix Platform, Predix Operations Optimization for IIoT, and etch-process control at nanometer level using big data and machine learning technologies in the semiconductor industry. He holds an MS in computer science from Texas A&M University Corpus Christi.
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