Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

12-2016

Abstract

Metro has become the first choice of traveling for tourists and citizens in metropolis due to its efficiency and convenience. Yet passengers have to rely on metro broadcasts to know their locations because popular localization services (e.g. GPS and wireless localization technologies) are often inaccessible underground. To this end, we propose MetroEye, an intelligent smartphone-based tracking system for metro passengers underground. MetroEye leverages low-power sensors embedded in modern smartphones to record ambient contextual features, and infers the state of passengers (Stop, Running, and Interchange) during an entire metro trip using a Conditional Random Field (CRF) model. MetroEye further provides arrival alarm services based on individual passenger state, and aggregates crowdsourced interchange durations to guide passengers for intelligent metro trip planning. Experimental results within 6 months across over 14 subway trains in 3 major cities demonstrate that MetroEye yields an overall accuracy of 80.5% outperforming the state-of-the-art.

Keywords

underground public transport, location-based service, smartphone, crowdsourcing

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, Hiroshima, Japan, 2016 November 28 - December 1

First Page

84

Last Page

93

Identifier

10.1145/2994374.2994381

Publisher

ACM

City or Country

Hiroshima, Japan

Additional URL

https://doi.org/10.1145/2994374.2994381

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