Automatically characterizing places with opportunistic crowdsensing using smartphones

Yohan Chon, Nicholas D. Lane, Fan Li, Hojung Cha, Feng Zhao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

191 Citations (Scopus)

Abstract

Automated and scalable approaches for understanding the semantics of places are critical to improving both existing and emerging mobile services. In this paper, we present CrowdSense@Place (CSP), a framework that exploits a previously untapped resource - opportunistically captured images and audio clips from smartphones - to link place visits with place categories (e.g., store, restaurant). CSP combines signals based on location and user trajectories (using WiFi/GPS) along with various visual and audio place "hints" mined from opportunistic sensor data. Place hints include words spoken by people, text written on signs or objects recognized in the environment. We evaluate CSP with a sevenweek, 36-user experiment involving 1,241 places in five locations around the world. Our results show that CSP can classify places into a variety of categories with an overall accuracy of 69%, outperforming currently available alternative solutions.

Original languageEnglish
Title of host publicationUbiComp'12 - Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Pages481-490
Number of pages10
DOIs
Publication statusPublished - 2012
Event14th International Conference on Ubiquitous Computing, UbiComp 2012 - Pittsburgh, PA, United States
Duration: 2012 Sep 52012 Sep 8

Publication series

NameUbiComp'12 - Proceedings of the 2012 ACM Conference on Ubiquitous Computing

Other

Other14th International Conference on Ubiquitous Computing, UbiComp 2012
CountryUnited States
CityPittsburgh, PA
Period12/9/512/9/8

All Science Journal Classification (ASJC) codes

  • Software

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  • Cite this

    Chon, Y., Lane, N. D., Li, F., Cha, H., & Zhao, F. (2012). Automatically characterizing places with opportunistic crowdsensing using smartphones. In UbiComp'12 - Proceedings of the 2012 ACM Conference on Ubiquitous Computing (pp. 481-490). (UbiComp'12 - Proceedings of the 2012 ACM Conference on Ubiquitous Computing). https://doi.org/10.1145/2370216.2370288