uCertify

Hands-On Industrial Internet of Things

(INDUSTRL-IOT.AJ1)
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1

Introduction

  • Who this course is for
  • What this course covers
  • To get the most out of this course
  • Conventions used
2

Introduction to Industrial IoT

  • IoT background
  • IoT use cases
  • IoT key technologies
  • What is the IIoT?
  • Summary
3

Understanding the Industrial Process and Devices

  • The industrial process
  • The CIM pyramid
  • The IIoT data flow
  • Summary
4

Industrial Data Flow and Devices

  • The IIoT data flow in the factory
  • Measurements and the actuator chain
  • Controllers
  • Industrial protocols
  • Supervisory control and data acquisition (SCADA)
  • Historian
  • ERP and MES
  • Summary
5

Implementing the Industrial IoT Data Flow

  • Discovering OPC
  • Understanding the IIoT edge
  • The edge architecture
  • Edge implementations
  • Edge internet protocols
  • Implementing the IIoT data flow
  • Edge deployment and data flow scenarios
  • Summary
6

Applying Cybersecurity

  • What is a DiD strategy?
  • Common control-network-segregation architectures
  • Securing the IIoT data flow
  • Summary
7

Performing an Exercise Based on Industrial Protocols and Standards

  • The OPC UA Simulation Server
  • The edge
  • Summary
8

Developing Industrial IoT and Architecture

  • Introduction to the IIoT platform and architectures
  • Microservice, containers, and serverless computing
  • The standard IIoT flow
  • Understanding the time-series technologies
  • Asset registry
  • Data processing and the analytics platform
  • Hands-on with InfluxDB, Node-RED, and OPC UA
  • Using Docker Compose and Docker Build
  • Summary
9

Implementing a Custom Industrial IoT Platform

  • An open source platform in practice
  • Building an asset registry to store asset information
  • Pros and cons of the proposed platform
  • Other technologies
  • Summary
10

Building an AWS Industrial IoT Solution

  • Why do we use commercial IIoT platforms?
  • IoT Core
  • Summary
11

Implementing an Industrial IOT Data Flow with AWS

  • Architecture of the exercise
  • AWS IoT Analytics
  • Storing data
  • Visualization
  • Summary
12

Performing a Practical Industrial IoT Solution with Azure

  • Azure IoT ecosystem
  • Registering for Azure IoT
  • Azure IoT Hub
  • Showing messages sent through Service Bus
  • Summary
13

Implementing an Industrial IoT Data Flow with Azure

  • Architecture of the proposed exercise
  • Setting the data flow
  • Building visualizations
  • Comparing the platforms
  • Summary
14

Performing Diagnostic, Maintenance, and Predictive Analytics

  • IIoT analytics
  • The different classes of analytics
  • IIoT analytics technologies
  • Building IIoT analytics
  • Understanding the role of the infrastructure
  • Deploying analytics
  • OSA
  • Analytics in practice
  • Summary
15

Implementing a Digital Twin – Advanced Analytics

  • Digital twins
  • AI and IoT
  • Developing a digital twin
  • Platforms for digital twins
  • Other kinds of IIoT data
  • Summary
16

Deploying an Analytics Model

  • Understanding model-as-a-service
  • Developing our first MaaS with MLflow
  • Working with the Azure ML service
  • Implementing analytics on Amazon SageMaker
  • Understanding GCP and multi-cloud solutions
  • Summary

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