Using Context Annotated Mobility Profiles to Recruit Data Collectors in Participatory Sensing

Authors:
Sasank Reddy;Katie Shilton;Jeff Burke;Deborah Estrin;Mark Hansen;Mani Srivastava
Affiliations:
Center for Embedded Networked Sensing (CENS), University of California, Los Angeles,;Center for Embedded Networked Sensing (CENS), University of California, Los Angeles,;Center for Embedded Networked Sensing (CENS), University of California, Los Angeles,;Center for Embedded Networked Sensing (CENS), University of California, Los Angeles,;Center for Embedded Networked Sensing (CENS), University of California, Los Angeles,;Center for Embedded Networked Sensing (CENS), University of California, Los Angeles,
Venue:
LoCA '09 Proceedings of the 4th International Symposium on Location and Context Awareness
Year:
2009

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Abstract

Mobile phones and accompanying network layers provide a platform to capture and share location, image, and acoustic data. This substrate enables participatory sensing: coordinated data gathering by individuals and communities to explore the world around them. Realizing such widespread and participatory sensing poses difficult challenges. In this paper, we discuss one particular challenge: creating a recruitment service to enable sensing organizers to select well-suited participants. Our approach concentrates on finding participants based on geographic and temporal coverage, as determined by context-annotated mobility profiles that model transportation mode, location, and time. We outline a three-stage recruitment framework designed to be parsimonious so as to limit risk to participants by reducing the location and context information revealed to the system. Finally, we illustrate the utility of the framework, along with corresponding modeling technique for mobility information, by analyzing data from a pilot mobility study consisting of ten users.