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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

Detecting unsafe drivers

Computer vision in machine learning has allowed us to tell if there are accidents on roads or unsafe work environments and can be used in conjunction with complex systems such as smart sales assistants. Computer vision has opened up many possibilities in IoT. Computer vision is also one of the most challenging from a cost perspective. In the next two recipes, we are going to discuss two different ways of using computer vision. The first one takes in large amounts of images generated from IoT devices and performs predictions and analysis on them using the high-performance distributed Databricks format. In the next recipe, we are going to use a technique for performing machine learning on edge devices with a small amount of compute using a low compute algorithm.

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