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Analytics for the Internet of Things (IoT)

You're reading from   Analytics for the Internet of Things (IoT) Intelligent analytics for your intelligent devices

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787120730
Length 378 pages
Edition 1st Edition
Languages
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Author (1):
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Andrew Minteer Andrew Minteer
Author Profile Icon Andrew Minteer
Andrew Minteer
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Table of Contents (14) Chapters Close

Preface 1. Defining IoT Analytics and Challenges FREE CHAPTER 2. IoT Devices and Networking Protocols 3. IoT Analytics for the Cloud 4. Creating an AWS Cloud Analytics Environment 5. Collecting All That Data - Strategies and Techniques 6. Getting to Know Your Data - Exploring IoT Data 7. Decorating Your Data - Adding External Datasets to Innovate 8. Communicating with Others - Visualization and Dashboarding 9. Applying Geospatial Analytics to IoT Data 10. Data Science for IoT Analytics 11. Strategies to Organize Data for Analytics 12. The Economics of IoT Analytics 13. Bringing It All Together

Solving industry-specific analysis problems


We will touch on a few industries to discuss special consideration for IoT data exploration and analysis.

Manufacturing

For IoT data generated during the manufacturing process, the accuracy of recorded values is especially important. Explore the data for outliers and analyze distributions carefully. Verify all the data ranges and distributions that you see with the experts on the manufacturing process.

The benefits of making sure the measurement values are clean as possible are two fold. First, any machine learning models created to detect problems will be significantly more accurate. Secondly, false positives due to invalid data can have a high penalty. The manufacturing line and product deliveries may be halted while the issue is investigated. In manufacturing, this can get expensive quickly. More perniciously, the long-term effect of false positives tends to be the complete rejection of the analytics by company management, when they no longer trust...

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