MetroEye: Towards fine-grained passenger tracking underground

Weixi Gu; Costas J. Spanos; Ming Jin; Lin Zhang; Zimu Zhou

doi:10.1145/2968219.2971437

MetroEye: Towards fine-grained passenger tracking underground

Weixi Gu, Costas J. Spanos, Ming Jin, Lin Zhang, Zimu Zhou

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

4 Citations (Scopus)

Abstract

Subway has become the first choice of traveling for people in metropolis due to its efficiency and convenience. Yet passengers have to rely on subway broadcasts to know their locations because popular localization services (e.g. GPS and wireless localization technologies) are often unavailable underground. To this end, we propose MetroEye, a finegrained passenger tracking service underground. MetroEye leverages smartphone sensors to record ambient contextual features, and infers the state of passengers (including stop, running, and interchange) during a 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 outperforms the state-of-The-Art. © 2016 ACM.

Original language	English
Title of host publication	UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing
Publisher	Association for Computing Machinery
Pages	77-80
ISBN (Print)	9781450344623
DOIs	https://doi.org/10.1145/2968219.2971437
Publication status	Published - 12 Sept 2016
Externally published	Yes
Event	2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016) - Heidelberg, Germany Duration: 12 Sept 2016 → 16 Sept 2016 https://www.ubicomp.org/ubicomp2016/

Publication series

Name	UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Conference

Conference	2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016)
Abbreviated title	UbiComp '16
Place	Germany
City	Heidelberg
Period	12/09/16 → 16/09/16
Internet address	https://www.ubicomp.org/ubicomp2016/

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

Context sensing
Crowdsourcing
Smartphone
Trip guide

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10.1145/2968219.2971437

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Gu, W., Spanos, C. J., Jin, M., Zhang, L., & Zhou, Z. (2016). MetroEye: Towards fine-grained passenger tracking underground. In UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 77-80). (UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing). Association for Computing Machinery. https://doi.org/10.1145/2968219.2971437

Gu, Weixi ; Spanos, Costas J. ; Jin, Ming et al. / MetroEye : Towards fine-grained passenger tracking underground. UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Association for Computing Machinery, 2016. pp. 77-80 (UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing).

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abstract = "Subway has become the first choice of traveling for people in metropolis due to its efficiency and convenience. Yet passengers have to rely on subway broadcasts to know their locations because popular localization services (e.g. GPS and wireless localization technologies) are often unavailable underground. To this end, we propose MetroEye, a finegrained passenger tracking service underground. MetroEye leverages smartphone sensors to record ambient contextual features, and infers the state of passengers (including stop, running, and interchange) during a 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 outperforms the state-of-The-Art. {\textcopyright} 2016 ACM.",

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Gu, W, Spanos, CJ, Jin, M, Zhang, L & Zhou, Z 2016, MetroEye: Towards fine-grained passenger tracking underground. in UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Association for Computing Machinery, pp. 77-80, 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016), Heidelberg, Germany, 12/09/16. https://doi.org/10.1145/2968219.2971437

MetroEye: Towards fine-grained passenger tracking underground. / Gu, Weixi; Spanos, Costas J.; Jin, Ming et al.
UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Association for Computing Machinery, 2016. p. 77-80 (UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - MetroEye

T2 - 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016)

AU - Gu, Weixi

AU - Spanos, Costas J.

AU - Jin, Ming

AU - Zhang, Lin

AU - Zhou, Zimu

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

PY - 2016/9/12

Y1 - 2016/9/12

N2 - Subway has become the first choice of traveling for people in metropolis due to its efficiency and convenience. Yet passengers have to rely on subway broadcasts to know their locations because popular localization services (e.g. GPS and wireless localization technologies) are often unavailable underground. To this end, we propose MetroEye, a finegrained passenger tracking service underground. MetroEye leverages smartphone sensors to record ambient contextual features, and infers the state of passengers (including stop, running, and interchange) during a 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 outperforms the state-of-The-Art. © 2016 ACM.

AB - Subway has become the first choice of traveling for people in metropolis due to its efficiency and convenience. Yet passengers have to rely on subway broadcasts to know their locations because popular localization services (e.g. GPS and wireless localization technologies) are often unavailable underground. To this end, we propose MetroEye, a finegrained passenger tracking service underground. MetroEye leverages smartphone sensors to record ambient contextual features, and infers the state of passengers (including stop, running, and interchange) during a 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 outperforms the state-of-The-Art. © 2016 ACM.

KW - Context sensing

KW - Crowdsourcing

KW - Smartphone

KW - Trip guide

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DO - 10.1145/2968219.2971437

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781450344623

T3 - UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

SP - 77

EP - 80

BT - UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

PB - Association for Computing Machinery

Y2 - 12 September 2016 through 16 September 2016

ER -

Gu W, Spanos CJ, Jin M, Zhang L, Zhou Z. MetroEye: Towards fine-grained passenger tracking underground. In UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Association for Computing Machinery. 2016. p. 77-80. (UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing). doi: 10.1145/2968219.2971437

MetroEye: Towards fine-grained passenger tracking underground

Abstract

Publication series

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Bibliographical note

Research Keywords

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