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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 the pollution reporting problem

From what you have learned in this chapter, you can now solve the IoT pollution sensor data by congressional districts problem introduced earlier. Follow these general steps using either Python code or spatial query functions in a database such as PostGIS:

  1. Download a shapefile for U.S. Interstates such as the U.S. National Transportation Atlas Interstate Highways shapefile available from the University of Iowa (ftp://ftp.igsb.uiowa.edu/gis_library/USA/us_interstates.htm).
  2. Download a shapefile for US congressional districts such as the TIGER/Line Shapefile available from the US Census (https://www.census.gov/cgi-bin/geo/shapefiles/index.php?year=2016&layergroup=Congressional+Districts+%28115%29).
  3. Load the shapefiles into a geospatial database using ogr2ogr or into Python using the fiona package.
  4. Add a 1 km buffer to the Interstates MultiLineString...
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