Graphical Model Approaches to Integrating Cell Tower and Spatial Data
Michael Kane
Owais Gilani
What is this talk about?
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There should be a "science of human mobility."
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Graphs are the right objects for capturing mobility at the population scale.
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Graphs based on mobility data "make sense" in a spatial sense.
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An application in pollution exposure
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Other applications (if there is time).
Human Mobility
The aggregate spatial movements of people at the population level in order to:
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understand the effect of environment condition on health (Eg. pollution exposure)
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determine the extent to which events like natural disasters affect community health (Eg. hurricanes)
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understand how diseases will spread in the general population
We measure mobility with cellphones
Call Detail Records (CDR) - produced by a telephone contains various attributes call, texts, and data transfer including time, duration, completion status, source and destination number, and location
Advanced Wireless Service (AWS) - produced by towers and contains tower id, anonymized device id, time, duration
Cell Towers and Your Phone
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Cell Towers and Your Phone
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Cell Towers and Your Phone
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Cell Towers and Your Phone
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AWS Advantages
Most complete
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passive collection
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avoids bias of CDR's
Location anonymization is inherent to the collection process
Provides a natural binning
How many towers are there?
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Mobility Graphs
Each tower is a vertex
Edges encode movement between tower locations
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Graphs as High-Dim. Objects
A mobility graph with \(n\) nodes can be represented as \(n \times n\) adjacency matrix \(M\) and has rank \(\leq n\).
Undirected: Focus on connectivity and is more appropriate for time-intervals at the period of cyclic activity.
Directed: Focus on migration and tells us about the transitions of group rather.
CT Connectivity Density
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CT Connectivity Communities
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Mobility Network Application: Environmental Ozone Exposure
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- Hourly ozone concentration (ppb)
- July 6 - August 5 2016
- 10 sites for model fit and 2 for validation
- 744 obs at each site
- About 10,000 towers
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Exposure Distribution
Difference Mobility vs. Static 8-hour Max Exposure Difference
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Less Exposure than Expected
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More Exposure than Expected
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Current Work
Taxonomy of types of mobility graph that can be constructed and application domains.
Disease models taking into account mobility:
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Yearly outbreaks - influenza
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Herd immunity - Measles
Time-series representations of mobility networks.
Thanks
NESS 2019
By Michael Kane
NESS 2019
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