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Hands-On Industrial Internet of Things

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

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781835887462
Length 530 pages
Edition 2nd Edition
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Authors (2):
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Antonio Capasso Antonio Capasso
Author Profile Icon Antonio Capasso
Antonio Capasso
Giacomo Veneri Giacomo Veneri
Author Profile Icon Giacomo Veneri
Giacomo Veneri
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Toc

Table of Contents (21) Chapters Close

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 20. Other Books You May Enjoy

Storing data

In a typical IIoT scenario, we want to process incoming data, but also store this data in a cloud storage system. We can receive from the device unstructured data, such as images, sounds, or logs, as well as events and sensor data. In our proposed IIoT architecture, we want to store sensor data, such as time-series data, but it is easy to extend these concepts to unstructured data as well. AWS supports time-series data with Amazon Timestream and Managed InfluxDB natively. For our exercise, we will use Timestream.

Timestream is a key-value-based NoSQL store service for high scalability. In this exercise, we are going to finalize our exercise by sending data from the edge to Timestream through IoT Core. In the next section, we will visualize the live data from Grafana.

Firstly, we need to search Timestream from the Services console:

Figure 10.26 – Locate Timestream

Figure 10.26 – Locate Timestream

Now, we need to create a database, create a table, and inject data...

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