| Source | Description | Access Method | | :--- | :--- | :--- | | | The original publisher's website. This is the most direct and supportive way to acquire the book, ensuring the author and publisher are compensated for their work. | Purchase directly from packtpub.com . | | Perlego | An online library service that offers a subscription model for accessing a vast range of textbooks and professional books. The PDF or ePub version is available as part of their subscription. | Subscribe to Perlego and access the book online or via their app. | | EBSCO | A major provider of research databases, e-journals, and e-books to libraries worldwide. Many university and public libraries provide access to this title through EBSCO's platforms. | Check your local or university library's online catalog. | | VitalSource | A leading platform for digital textbooks and course materials. You can purchase an e-book version that is readable on their Bookshelf app. | Purchase from vitalsource.com . | | Google Books | A limited preview of the book is often available on Google Books, allowing you to see the table of contents and some sample pages. | Search for the title on books.google.com . | | CSDN | A Chinese tech community site where a PDF version is available (note: verify licensing if used for official purposes). | Available for download with credits. | | GitHub | The official code repository for the book is hosted on GitHub, containing all the hands-on code examples and sometimes supplementary color images. | Visit github.com/PacktPublishing/Hands-on-Azure-Digital-Twins . |
The author even shares that he has designed and implemented a solution where data is collected from IoT and Microsoft Dynamics 365 Field Service, an Azure Digital Twins service is built up dynamically using Azure Functions, Azure Service Bus, and Logic Apps, and a 3D visual is generated using Microsoft HoloLens 2 as an augmentation device. alexander meijers handson azure digital twins pdf
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Industrial digital twins mirror complex production lines. By integrating historical data from Azure Data Explorer with machine learning models, factory floors can predict equipment failures before they happen, drastically minimizing costly downtime. Conclusion | | Perlego | An online library service
The final section concludes with various examples of digital twin solutions using Azure Digital Twins. For each solution, the book explains the scenario, a possible solution design, and architecture that will help you better understand how solutions to real-world challenges can be implemented using this technology. This practical approach is a hallmark of the book, emphasizing hands-on learning rather than just theoretical concepts.