You're reading from Architectural Patterns and Techniques for Developing IoT Solutions Build IoT applications using digital twins, gateways, rule engines, AI/ML integration, and related patterns

Product type Paperback

Published in Sep 2023

Publisher Packt

ISBN-13 9781803245492

Length 304 pages

Edition 1st Edition

Tools

Combine

Concepts

IoT Development

Author (1):

Jasbir Singh Dhaliwal

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Table of Contents (20) Chapters

Preface

1. Part 1: Understanding IoT Patterns

2. Chapter 1: Introduction to IoT Patterns FREE CHAPTER

3. Chapter 2: IoT Patterns for Field Devices

4. Chapter 3: IoT Patterns for the Central Server

5. Part 2: IoT Patterns in Action

6. Chapter 4: Pattern Implementation in the Consumer Domain

7. Chapter 5: Pattern Implementation in the Smart City Domain

8. Chapter 6: Pattern Implementation in the Retail Domain

9. Chapter 7: Pattern Implementation in the Manufacturing Domain

10. Chapter 8: Pattern Implementation in the Agriculture Domain

11. Part 3: Implementation Considerations

12. Chapter 9: Sensor and Actuator Selection Guidelines

13. Chapter 10: Analytics in the IoT Context

14. Chapter 11: Security in the IoT Context

15. Part 4: Extending IoT Solutions

16. Chapter 12: Exploring Synergies with Emerging Technologies

17. Chapter 13: Epilogue

18. Index

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AI/ML

AI/ML is a general term that encompasses a lot of other technologies, such as deep learning, LLMs, and generative AI. Here, it is represented as follows:

Figure 12.5 – AI/ML

AI/ML integration was described in detail as part of the AI/ML integration pattern in Chapter 3.

Benefits of combining IoT and AI/ML

One benefit of combining AI/ML with IoT is that you can ingest and process high-volume and velocity data produced by IoT sensors in almost real time to derive timely/actionable insights. In addition to efficiency and performance gains, integrating AI/ML with IoT will free decision-making from biases inherent in human thinking. As a result, the combination of these technologies would result in more efficient, timely, and accurate analysis, which is a major advancement over traditional static rules (if X, do Y) or algorithms.

AI/ML integration helps in improving the quality and accuracy of the raw data obtained from sensors by removing...