Overview
- Describes the architectural end-to-end picture of Azure components deployed in IoT projects
- Covers the linkage between device telemetry and data analysis
- Provides guidance on how to reduce time to market when deploying Microsoft IoT solution accelerators
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Table of contents (9 chapters)
Keywords
About this book
Microsoft-specific topics addressed include: deploying edge devices and pushing intelligence to the edge; connecting IoT devices to Azure and landing data there, applying Azure Machine Learning, analytics, and Cognitive Services; roles for Microsoft solution accelerators and managed solutions; and integration of the Azure footprint with legacy infrastructure.
The book concludes with a discussion of best practices in defining and developing solutions and creating a plan for success.
What You Will Learn
- Design the right IoT architecture to deliver solutions for a variety of project needs
- Connect IoT devices to Azure for data collection and delivery of services
- Use Azure Machine Learning and Cognitive Services to deliver intelligence in cloud-based solutions and at the edge
- Understand the benefits and tradeoffs of Microsoft's solution accelerators and managed solutions
- Investigate new use cases that are described and apply best practices in deployment strategies
- Integrate cutting-edge Azure deployments with existing legacy data sources
Who This Book Is For
Developers and architects new to IoT projects or new to Microsoft Azure IoT components as well as readers interested in best practices used in architecting IoT solutions that utilize the Azure platform
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Azure Internet of Things Revealed
Book Subtitle: Architecture and Fundamentals
Authors: Robert Stackowiak
DOI: https://doi.org/10.1007/978-1-4842-5470-7
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Robert Stackowiak 2019
Softcover ISBN: 978-1-4842-5469-1Published: 10 November 2019
eBook ISBN: 978-1-4842-5470-7Published: 09 November 2019
Edition Number: 1
Number of Pages: XV, 205
Number of Illustrations: 96 b/w illustrations
Topics: Microsoft and .NET, Machine Learning