Industrial Internet Application Development

More Information
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
About

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.

 

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
Page Count 412
Course Length 12 hours 21 minutes
ISBN 9781788298599
Date Of Publication 28 Sep 2018

Authors

Prashant Tyagi

Prashant Tyagi is responsible for enabling the big data strategy at GE Digital for the Industrial Internet that leverages IT and Operational data for predictive analytics. He works with all the P&L verticals (such as oil and gas, power generation, aviation, healthcare, and so on) to enable their IoT use cases on the data and analytics platform. Prior to GE, he was with Cisco, where he was leading the organization, focused on delivering platform solutions for Cisco’s smart services. Before Cisco he co-founded a company focused on delivering intelligent drug discovery data platforms for the biotech and pharma industries. He is on the board of ISSIP, a non-profit cross academia and industry organization, focused on service innovation. He leads a cross-industry special interest group (SIG) on IoT and analytics, and is an advisor to the open source fog computing initiative, ioFog, an Eclipse foundation initiative. Prashant holds a B.Tech from Indian Institute of Technology (IIT) Delhi, an MBA from the Indian Institute of Management (IIM), Bangalore, and an MS in Computer Science from Clemson University. He has publications in leading journals and magazines on IoT, analytics, and data strategy. Prashant is a renowned public speaker and panelist at several conferences.

Jayant Thomas

Jayant Thomas (JT) is the director of software engineering for the IoT apps for GE Digital. He is responsible for building IoT SaaS applications using the Predix platform, and specializes in building microservices-based architecture, reactive, event-driven systems. JT holds a masters in technology from NIIT and MBA in technology from UC Davis, CA, and has 12 patents in the speech language processing, multimodal application, and cloud architectures. When not hacking code, JT spends time with kids and enjoys crossfit training and kickboxing.

Kishore Reddipalli

 Kishore Reddipalli is a software technical director and expert in building IIoT big data and cloud computing platform and products at ultra scale. He is passionate in building software for analytics and machine learning to make it simplified for authoring the algorithms from inception to production at scale. He is a speaker in large global conferences in Big data technologies. Over the years he provided leadership in various capacities ranging from Software Engineer to Director of Engineering and Architecture for development of platforms and products in multiple domains such as for clinical decision support system, electronic medical records in healthcare, Predix Platform, Predix Operations Optimization for industrial IoT, Etch Process control at nano meter level using big data & machine learning technologies in Semiconductor Industry. He holds a M.S. in Computer Science from Texas A&M University CC

Alena Traukina

Alena Traukina is IoT practice Lead at Altoros. She has over 12 years of experience in 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, Elena has served in different capacities, ranging from software engineer to software engineering manager and the head of Altoros’s Ruby Department. She is also one of the first GE's Predix Influencers.