Seeing our signals: combining location traces and web-based models for personal discovery

Authors:
E. Agapie;G. Chen;D. Houston;E. Howard;J. Kim;M. Y. Mun;A. Mondschein;S. Reddy;R. Rosario;J. Ryder;A. Steiner;J. Burke;E. Estrin;M. Hansen;M. Rahimi
Affiliations:
Center for Embedded Networked Sensing, Los Angeles, CA;Center for Embedded Networked Sensing, Los Angeles, CA;UCLA Institute of Transportation Studies, Los Angeles, CA;Center for Embedded Networked Sensing, Los Angeles, CA;Center for Embedded Networked Sensing, Los Angeles, CA;Center for Embedded Networked Sensing, Los Angeles, CA;Center for Embedded Networked Sensing, Los Angeles, CA and UCLA Institute of Transportation Studies, Los Angeles, CA;Center for Embedded Networked Sensing, Los Angeles, CA;Center for Embedded Networked Sensing, Los Angeles, CA;Center for Embedded Networked Sensing, Los Angeles, CA;Center for Embedded Networked Sensing, Los Angeles, CA;Center for Embedded Networked Sensing, Los Angeles, CA and UCLA Center for Research in Engineering, Los Angeles, CA;Center for Embedded Networked Sensing, Los Angeles, CA;Center for Embedded Networked Sensing, Los Angeles, CA;Center for Embedded Networked Sensing, Los Angeles, CA
Venue:
Proceedings of the 9th workshop on Mobile computing systems and applications
Year:
2008

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Abstract

Each of us has a complex and reciprocal relationship with our environment. Based on limited knowledge of this interwoven set of influences and consequences, we constantly make choices: where to live, how to go to work, what brands to buy, what to do with our leisure time. These choices evolve into patterns, and these patterns become driving functions of our relationship with the world around us. With increasing ease, devices we carry can sense, process, and transmit data on these patterns for our own use or to share, carefully, with others. In particular, here we will focus on location time series, gathered from GPS-enabled personal mobile devices. From this capacity emerges a new class of hybrid mobile-web applications that, first, enable personal exploration of our own patterns and, second, use the same data to index our life into other available datasets about the world around us. Such applications, revealing the previously unobservable about our own lives, offer an opportunity to employ mobile technology to illuminate the ramifications of our choices on others and the effects of the "microenvironments" we move through on us [1, 10].