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You're reading from  Hands-On Industrial Internet of Things

Product typeBook
Published inNov 2018
PublisherPackt
ISBN-139781789537222
Edition1st Edition
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Authors (2):
Giacomo Veneri
Giacomo Veneri
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Giacomo Veneri

Giacomo Veneri graduated in computer science from the University of Siena. He holds a PhD in neuroscience context with various scientific publications. He is Predix Cloud certified and an influencer, as well as SCRUM and Oracle Java certified. He has 18 years' experience as an IT architect and team leader. He has been an expert on IoT in the fields of oil and gas and transportation since 2013. He lives in Tuscany, where he loves cycling.
Read more about Giacomo Veneri

Antonio Capasso
Antonio Capasso
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Antonio Capasso

Antonio Capasso graduated in computer automation in 1999 and computer science in 2003 from the University of Naples. He has been working for twenty years on large and complex IT projects related to the industrial world in a variety of fields (automotive, pharma, food and beverage, and oil and gas), in a variety of roles (programmer, analyst, architect, and team leader) with different technologies and software. Since 2011, he has been involved in building and securing industrial IoT infrastructure. He currently lives in Tuscany, where he loves trekking and swimming.
Read more about Antonio Capasso

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Developing Industrial IoT and Architecture

In this chapter, we will learn about the basic technologies required to develop an I-IoT platform. We will look at different use cases and how these affect your choice of technology.

We will cover the following topics:

  • Introduction to the I-IoT platform and architectures
  • Open Service Gateway Initiative (OSGi), microservices, containers, and serverless computing
  • The standard I-IoT flow

Technical requirements

Introduction to the I-IoT platform and architectures

From an architectural point of view, an IoT platform presents significant challenges:

  • The amount of data acquired, ingested, and processed requires high bandwidth, storage, and computational capabilities
  • The devices are distributed across a vast geographical area
  • Businesses require their architecture to be evolutionary so that new services and capabilities can be added daily to deploy to customers

More so than other standard applications, flexibility and scalability are vital to a typical IoT platform. However, IoT and I-IoT both have an interesting benefit, which is the fact that the relationships between the actors are weak. In the IoT platform, signals are independent. Data sharding can be used for storing purposes and parallel computation can be used to improve computational performance. On a typical ERP or e-commerce...

OSGi, microservice, containers, and serverless computing

When the I-IoT application was being developed in 2010, the decision was made to use Apache Karaf, Java, RabbitMQ, Redis, and a historical NoSQL database. Apache Karaf is an OSGi application server. OSGi Alliance was founded in 1999 but only became popular in 2008. The OSGi specification, which is currently version 7.0, describes a service platform and modular system for the Java programming language that implements a complete and dynamic component model. In an OSGi framework, the same bundle (the deployment component of an application) can coexist with different versions. A strong security mechanism allows you to define the boundaries of the application, thereby avoiding unwanted spaghetti architecture. These concepts were adopted by Java 9.

OSGi was chosen due to its high degree of modularity. However, after two years...

The standard I-IoT flow

In Chapter 2, Understanding the Industrial Process and Devices, we looked at how industrial data is generated, gathered, and transferred to the cloud by familiarizing ourselves with computer-integrated manufacturing (CIM). We also looked at industrial equipment, such as DCS, PLCs, and SCADA, and network protocols, such as Fieldbus, ControlBus, and OPC. This gave us a picture of the whole path of industrial signals, from when they are generated by sensors in a factory to when they are processed in the cloud. In Chapter 3, Industrial Data Flow and Devices, and Chapter 4, Implementing the Industrial IoT Data Flow, we talked in detail about data acquisition, data sources, related protocols, and the edge devices used to push data into the cloud. This has shown us how data acquisition is the foundation of the I-IoT and how we need to be compliant with several...

Summary

In this chapter, we looked at the basic concepts of I-IoT data-processing. We learned about the key principles of data storage, including time-series, asset-management using asset registry, and data-processing with analytics and Digital Twin.

In the next chapter, we will build a real I-IoT solution based on common open source technologies.

Questions

  1. What are the main differences between the microservices and monolithic architectures?
    1. Microservices are small services that can be deployed separately
    2. Monolithic applications improve modularity but not scalability
    3. Microservices perform better than monolithic architectures
  2. True or false: Docker is the primary technology used to build microservices.
    1. True
    2. False
  3. What is an asset registry?
    1. A SQL database to store time-series
    2. A NoSQL database to store static information about devices monitored
    3. A repository that stores information about assets and measures

Further reading

Check out the following links for more information:

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Authors (2)

author image
Giacomo Veneri

Giacomo Veneri graduated in computer science from the University of Siena. He holds a PhD in neuroscience context with various scientific publications. He is Predix Cloud certified and an influencer, as well as SCRUM and Oracle Java certified. He has 18 years' experience as an IT architect and team leader. He has been an expert on IoT in the fields of oil and gas and transportation since 2013. He lives in Tuscany, where he loves cycling.
Read more about Giacomo Veneri

author image
Antonio Capasso

Antonio Capasso graduated in computer automation in 1999 and computer science in 2003 from the University of Naples. He has been working for twenty years on large and complex IT projects related to the industrial world in a variety of fields (automotive, pharma, food and beverage, and oil and gas), in a variety of roles (programmer, analyst, architect, and team leader) with different technologies and software. Since 2011, he has been involved in building and securing industrial IoT infrastructure. He currently lives in Tuscany, where he loves trekking and swimming.
Read more about Antonio Capasso