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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

Adding external datasets


There is a wide variety of useful external datasets available to download and integrate into your IoT analytics, often for free. There are far too many of these to do an exhaustive tour, but we will touch on some useful examples. Using these datasets is a great low-cost way to enhance the value of your IoT data.

External datasets - geography

You have IoT devices distributed across many locations. Location is now an attribute that can allow you to find patterns in the data, which you can then monetize. The environment, the demographics in the area, the local economic conditions, and the weather can all be tied to the geographic location of the device. Use geographic datasets to enhance the potential value of your IoT data.

Elevation

Elevation can be an important attribute in many situations as it is tied to the operating conditions of the device and the surrounding environment. Even if your device does not move, it can still be valuable to know its elevation. The maker...

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