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Artificial Intelligence for IoT Cookbook

You're reading from   Artificial Intelligence for IoT Cookbook Over 70 recipes for building AI solutions for smart homes, industrial IoT, and smart cities

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Product type Paperback
Published in Mar 2021
Publisher Packt
ISBN-13 9781838981983
Length 260 pages
Edition 1st Edition
Languages
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Author (1):
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Michael Roshak Michael Roshak
Author Profile Icon Michael Roshak
Michael Roshak
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Toc

Table of Contents (11) Chapters Close

Preface 1. Setting Up the IoT and AI Environment 2. Handling Data FREE CHAPTER 3. Machine Learning for IoT 4. Deep Learning for Predictive Maintenance 5. Anomaly Detection 6. Computer Vision 7. NLP and Bots for Self-Ordering Kiosks 8. Optimizing with Microcontrollers and Pipelines 9. Deploying to the Edge 10. About Packt

Dealing with BOM changes

Bill of Materials (BOMs) are the components that make up the device. These can be resistors, chips, and other components. The life cycle of a typical IoT product is about 10 years. In that time, things can change with the product. A component manufacturer could discontinue a part such as a chip line. Outsourced manufacturers typically perform BOM optimization on a board layout, though BOM optimization can change the quality of the device. For example, it can change the sensitivity of the sensor or the lifetime of a device.

This can throw off trained models and can have a dramatic effect on any remaining useful life calculations and predictive maintenance models. When working with IoT and machine learning, tracking changes that have been made to any remaining useful life based on BOM and factory changes can help us detect issues with the quality and longevity of a device.

This is typically done with a database. When a device is made in a factory, that device...

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