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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 spikes with streaming analytics

Stream Analytics is a tool that connects IoT Hub to other resources within Azure using a SQL interface. Stream Analytics moves data from IoT Hub to Cosmos DB, storage blobs, serverless functions, or a number of other scalable options. Streaming analytics has a few functions built-in, and you can create more functions yourself using JavaScript; anomaly detection is one of those functions. In this example, we are going to use Raspberry Pi to stream gyroscope and acceleration data to IoT Hub. Then we'll connect streaming analytics and, using its SQL interface, we will output only the anomalous results.

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