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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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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
Deep Learning for Predictive Maintenance

Predictive maintenance is one of the most sought after machine learning solutions for IoT. It is also one of the most elusive machine learning solutions for IoT. Other areas of machine learning can easily be solved, implementing Computer Vision, for example, can be done in hours using tools such as OpenCV or Keras. To be successful with predictive maintenance you first need the right sensors. The Data collection design recipe in Chapter 2, Handling Data, can be used to help determine proper sensor placement. The Exploratory factor analysts recipe in Chapter 2, Handling Data can help determine the cadence with which the data needs to be stored. One of the biggest hurdles to implementing predictive maintenance is that there needs to be a sufficient amount of device failures. For rugged industrial devices, this can take...

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