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Analytics for the Internet of Things (IoT)

You're reading from  Analytics for the Internet of Things (IoT)

Product type Book
Published in Jul 2017
Publisher Packt
ISBN-13 9781787120730
Pages 378 pages
Edition 1st Edition
Languages
Author (1):
Andrew Minteer Andrew Minteer
Profile icon Andrew Minteer

Table of Contents (20) Chapters

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Defining IoT Analytics and Challenges IoT Devices and Networking Protocols IoT Analytics for the Cloud Creating an AWS Cloud Analytics Environment Collecting All That Data - Strategies and Techniques Getting to Know Your Data - Exploring IoT Data Decorating Your Data - Adding External Datasets to Innovate Communicating with Others - Visualization and Dashboarding Applying Geospatial Analytics to IoT Data Data Science for IoT Analytics Strategies to Organize Data for Analytics The Economics of IoT Analytics Bringing It All Together

Vector-based methods


There are two main categories of geospatial analysis and file types, vector and raster. Vectors are all about shapes, while rasters are more about grids. Vector is more common due to flexibility and efficient storage. Vectors can be defined simply by using a set of points. There are three main types of vector geometry:

  • Points: This can be defined in two or three dimensions. It is the common latitude, longitude pair you are probably very familiar with. The airport locations used in the R code previously are examples of points.
  • Lines or LineString: A LineString is defined by a set of points and order is important. More than one LineString can be stored together; in that case it is called, unsurprisingly, a MultiLineString. A river system or roadways network is an example of a MultiLineString. A file that contains a MultiLineString for the US Interstate roadways network can be downloaded from the University of Iowa GIS Library (ftp://ftp.igsb.uiowa.edu/gis_library/USA/us_interstates...
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