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CMU-HCII-12-107
Human-Computer Interaction Institute
School of Computer Science, Carnegie Mellon University
CMU-HCII-12-107
Using Social Technologies to Increase
Sharing and Communication around Household Energy Consumption
in Low-Income and Rental Communities
Tawanna Dillahunt
November 2012
Ph.D. Thesis
CMU-HCII-12-107.pdf
Keywords:
Home energy consumption, eco-feedback technologies, low-income,
social computing, fieldstudies,
community, privacy, concept validation, ubiquitous computing, human-computer
interaction.
The behavioral impacts of providing users with real-time energy use
feedback—even at the aggregate level—can reduce energy use by 10-15%.
Though comparison is a feedback method
shown to encourage additional savings, home-energy research studies exploring
social communication around feedback devices are limited. As a result, the
relationship between feedback technologies and energy-conservation behaviors
has become an increasingly important focus in the field of human-computer
interaction. Furthermore, few studies explore this phenomenon among
households, specifically, low-income households.
To bridge this gap, we conducted 26 photo-elicitation interviews with
low-income tenant households across two locations, Pittsburgh, PA and
eastern NC. Our studies of low-income households show that comparison
across households can have an important impact on how energy is used
(or saved). These studies also reveal conflict between various internal and
external stakeholders such as family members and landlords. To better
understand this conflict, we re-analyzed data from the first study for
specific landlord/tenant conflicts and resolutions, held semi-structured
interviews with landlords to understand their perspectives, and held a
role-play exercise with tenants to understand ways to resolve the conflicts
between landlords and tenants. Finally, based on our qualitative study
results, we developed an Android-based application called the Community
Monitor that supports comparison and provides household energy-use information. After conducting a longitudinal energy use study with 15 collocated
U.S. households in Pittsburgh, PA, we were able to better understand the
impact of engagement around social sharing and community energy monitoring in residential communities, identify
energy-related and personal concerns, and provide design implications for
home-energy applications that share consumption data among community members.
197 pages
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