You're reading from Hands-On Industrial Internet of Things Build robust industrial IoT infrastructure by using the cloud and artificial intelligence

Product type Paperback

Published in Nov 2024

Publisher Packt

ISBN-13 9781835887462

Length 530 pages

Edition 2nd Edition

Concepts

Industrial Internet of Things

Authors (2):

Antonio Capasso

Giacomo Veneri

View More author details

Table of Contents (21) Chapters

Preface

1. Part 1:Industrial IoT

2. Chapter 1: Introduction to Industrial IoT FREE CHAPTER

3. Chapter 2: Understanding the Industrial Process and Devices

4. Chapter 3: Industrial Data Flow and Devices

5. Chapter 4: Implementing the Industrial IoT Data Flow

6. Chapter 5: Applying Cybersecurity

7. Chapter 6: Performing an Exercise Based on Industrial Protocols and Standards

8. Part 2:Industrial IoT Architecture

9. Chapter 7: Developing Industrial IoT and Architecture

10. Chapter 8: Implementing a Custom Industrial IoT Platform

11. Chapter 9: Building an AWS Industrial IoT Solution

12. Chapter 10: Implementing an Industrial IOT Data Flow with AWS

13. Chapter 11: Performing a Practical Industrial IoT Solution with Azure

14. Chapter 12: Implementing an Industrial IoT Data Flow with Azure

15. Part 3:Industrial Artificial Intelligence of Things

16. Chapter 13: Performing Diagnostic, Maintenance, and Predictive Analytics

17. Chapter 14: Implementing a Digital Twin – Advanced Analytics

18. Chapter 15: Deploying an Analytics Model

19. Index

Why subscribe?

20. Other Books You May Enjoy

Building visualizations

Visualization is the last component of our architecture. Through visualization applications, users can monitor the status of assets and alarms and build powerful dashboards. Azure offers several options for data visualization:

Azure Data Explorer
Managed Grafana
Power BI
Azure IoT Central

We have already seen Grafana in Chapters 8 and 10. In a later subsection, we will see the basic steps to configure it.

Azure Data Explorer

Azure Data Explorer is a managed service to efficiently handle data. Azure Data Explorer allows us to process, export, and visualize data. Data can be locally stored or simply connected through connectors. Connectors support IoT Hub, Cosmos DB, Event Hubs, and Event Grid. Moreover, we can use an ingestion SDK to connect different data sources.

Finally, we can manage data efficiently using a powerful query language called Kusto Query Language (KQL).

To work with Azure Data Explorer, search for it in...