Book Image

Hands-On Azure Digital Twins

By : Alexander Meijers
Book Image

Hands-On Azure Digital Twins

By: Alexander Meijers

Overview of this book

In today’s world, clients are using more and more IoT sensors to monitor their business processes and assets. Think about collecting information such as pressure in an engine, the temperature, or a light switch being turned on or off in a room. The data collected can be used to create smart solutions for predicting future trends, creating simulations, and drawing insights using visualizations. This makes it beneficial for organizations to make digital twins, which are digital replicas of the real environment, to support these smart solutions. This book will help you understand the concept of digital twins and how it can be implemented using an Azure service called Azure Digital Twins. Starting with the requirements and installation of the Azure Digital Twins service, the book will explain the definition language used for modeling digital twins. From there, you'll go through each step of building digital twins using Azure Digital Twins and learn about the different SDKs and APIs and how to use them with several Azure services. Finally, you'll learn how digital twins can be used in practice with the help of several real-world scenarios. By the end of this book, you'll be confident in building and designing digital twins and integrating them with various Azure services.
Table of Contents (25 chapters)
1
Section 1: Azure Digital Twin Essentials
4
Section 2: Getting Started with Azure Digital Twins
11
Section 3: Digital Twins Advanced Techniques
19
Section 4: Digital Twin Implementations in Real-world Scenarios

Understanding ontologies

Building a first model requires defining all the models and their underlying relationships with your digital twin. Starting a digital twin from scratch can be a very time-consuming undertaking. It requires the identification of the different entities that play a role within the digital twin. Additionally, it also requires thinking about what properties and relationships we need to consider to have our digital twin deliver what we want.

The building of digital twins is often bound to a certain industry, or a part of that industry. Industry-built digital twins are all about modeling complex systems with a lot of different assets, properties, and relationships.

Wouldn't it be great to start with a predefined set of models that suits your needs? That would make it far easier to design a digital twin. We could extend such a predefined set of models in order to accommodate our own needs. To do this, we need to use ontologies.

An ontology is a structure...