Understanding the coverage and scalability of place-centric crowdsensing

Yohan Chon, Nicholas D. Lane, Yunjong Kim, Feng Zhao, Hojung Cha

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

100 Citations (Scopus)

Abstract

Crowd-enabled place-centric systems gather and reason over large mobile sensor datasets and target everyday user locations (such as stores, workplaces, and restaurants). Such systems are transforming various consumer services (for example, local search) and data-driven organizations (city planning). As the demand for these systems increases, our understanding of how to design and deploy successful crowdsensing systems must improve. In this paper, we present a systematic study of the coverage and scaling properties of placecentric crowdsensing. During a two-month deployment, we collected smartphone sensor data from 85 participants using a representative crowdsensing system that captures ≈ 48,000 different place visits. Our analysis of this dataset examines issues of core interest to place-centric crowdsensing, including place-temporal coverage, the relationship between the user population and coverage, privacy concerns, and the characterization of the collected data. Collectively, our findings provide valuable insights to guide the building of future placecentric crowdsensing systems and applications.

Original languageEnglish
Title of host publicationUbiComp 2013 - Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing
Pages3-12
Number of pages10
DOIs
Publication statusPublished - 2013 Oct 15
Event2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2013 - Zurich, Switzerland
Duration: 2013 Sep 82013 Sep 12

Other

Other2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2013
CountrySwitzerland
CityZurich
Period13/9/813/9/12

All Science Journal Classification (ASJC) codes

  • Software

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    Chon, Y., Lane, N. D., Kim, Y., Zhao, F., & Cha, H. (2013). Understanding the coverage and scalability of place-centric crowdsensing. In UbiComp 2013 - Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 3-12) https://doi.org/10.1145/2493432.2493498