Making Sense of Sensor Data: How Local Environmental Conditions Add Value to Social Science Research

Recent advances in computing technologies have enabled the development of low-cost, compact weather and air quality monitors. The U.S. federally funded Array of Things (AoT) project has deployed more than 140 such sensor nodes throughout the City of Chicago. This article combines a year’s worth of A...

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Bibliographic Details
Published in:Social science computer review 2022-02, Vol.40 (1), p.179-194
Main Authors: English, Ned, Zhao, Chang, Brown, Kevin L., Catlett, Charlie, Cagney, Kathleen
Format: Article
Language:English
Subjects:
Air pollution
Air quality
Data
Dementia
Mental health
Nodes
Outdoor air quality
Pollutants
Science and technology
Sensors
Social research
Social sciences
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Summary:Recent advances in computing technologies have enabled the development of low-cost, compact weather and air quality monitors. The U.S. federally funded Array of Things (AoT) project has deployed more than 140 such sensor nodes throughout the City of Chicago. This article combines a year’s worth of AoT sensor data with household data collected from 450 elderly Chicagoans in order to explore the feasibility of using previously unavailable data on local environmental conditions to improve traditional neighborhood research. Specifically, we pilot the use of AoT sensor data to overcome limitations in research linking air pollution to poor physical and mental health and find support for recent findings that exposure to pollutants contributes to both respiratory- and dementia-related diseases. We expect that this support will become even stronger as sensing technologies continue to improve and more AoT nodes come online, enabling additional applications to social science research where environmental context matters.
ISSN:0894-4393
1552-8286
DOI:10.1177/0894439320920601