No longer sleeping with a bomb: A duet system for protecting urban safety from dangerous goods

Jingyuan Wang; Chao Chen; Junjie Wu; Zhang Xiong

doi:10.1145/3097983.3097985

No longer sleeping with a bomb: A duet system for protecting urban safety from dangerous goods

Jingyuan Wang
, Chao Chen
, Junjie Wu^*
, Zhang Xiong

^*Corresponding author for this work

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

28 Scopus citations

Abstract

Recent years have witnessed the continuous growth of megalopolises worldwide, which makes urban safety a top priority in modern city life. Among various threats, dangerous goods such as gas and hazardous chemicals transported through and around cities have increasingly become the deadly "bomb" we sleep with every day. In both academia and government, tremendous efforts have been dedicated to dealing with dangerous goods transportation (DGT) issues, but further study is still in great need to quantify the problem and explore its intrinsic dynamics in a big data perspective. In this paper, we present a novel system called DGEYE, which features a "duet" between DGT trajectory data and human mobility data for risky zones identification. Moreover, DGEYE innovatively takes risky patterns as the keystones in DGT management, and builds causality networks among them for pain points identification, attribution and prediction. Experiments on both Beijing and Tianjin cities demonstrate the effectiveness of DGEYE. In particular, the report generated by DGEYE driven the Beijing government to lay down gas pipelines for the famous Guijie food street.

Original language	English
Title of host publication	KDD 2017 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Publisher	Association for Computing Machinery
Pages	1673-1681
Number of pages	9
ISBN (Electronic)	9781450348874
DOIs	https://doi.org/10.1145/3097983.3097985
State	Published - 13 Aug 2017
Event	23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2017 - Halifax, Canada Duration: 13 Aug 2017 → 17 Aug 2017

Publication series

Name	Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Volume	Part F129685

Conference

Conference	23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2017
Country/Territory	Canada
City	Halifax
Period	13/08/17 → 17/08/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities
SDG 12 Responsible Consumption and Production

Keywords

Causal analysis
Intelligent transportation
Pattern mining
Urban safety

Access to Document

10.1145/3097983.3097985

Cite this

Wang, J., Chen, C., Wu, J., & Xiong, Z. (2017). No longer sleeping with a bomb: A duet system for protecting urban safety from dangerous goods. In KDD 2017 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 1673-1681). (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Vol. Part F129685). Association for Computing Machinery . https://doi.org/10.1145/3097983.3097985

Wang, Jingyuan ; Chen, Chao ; Wu, Junjie et al. / No longer sleeping with a bomb : A duet system for protecting urban safety from dangerous goods. KDD 2017 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery , 2017. pp. 1673-1681 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

@inproceedings{1268034229814a74924a527d49477249,

title = "No longer sleeping with a bomb: A duet system for protecting urban safety from dangerous goods",

abstract = "Recent years have witnessed the continuous growth of megalopolises worldwide, which makes urban safety a top priority in modern city life. Among various threats, dangerous goods such as gas and hazardous chemicals transported through and around cities have increasingly become the deadly {"}bomb{"} we sleep with every day. In both academia and government, tremendous efforts have been dedicated to dealing with dangerous goods transportation (DGT) issues, but further study is still in great need to quantify the problem and explore its intrinsic dynamics in a big data perspective. In this paper, we present a novel system called DGEYE, which features a {"}duet{"} between DGT trajectory data and human mobility data for risky zones identification. Moreover, DGEYE innovatively takes risky patterns as the keystones in DGT management, and builds causality networks among them for pain points identification, attribution and prediction. Experiments on both Beijing and Tianjin cities demonstrate the effectiveness of DGEYE. In particular, the report generated by DGEYE driven the Beijing government to lay down gas pipelines for the famous Guijie food street.",

keywords = "Causal analysis, Intelligent transportation, Pattern mining, Urban safety",

author = "Jingyuan Wang and Chao Chen and Junjie Wu and Zhang Xiong",

note = "Publisher Copyright: {\textcopyright} 2017 ACM.; 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2017 ; Conference date: 13-08-2017 Through 17-08-2017",

year = "2017",

month = aug,

day = "13",

doi = "10.1145/3097983.3097985",

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series = "Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining",

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Wang, J, Chen, C, Wu, J & Xiong, Z 2017, No longer sleeping with a bomb: A duet system for protecting urban safety from dangerous goods. in KDD 2017 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, vol. Part F129685, Association for Computing Machinery , pp. 1673-1681, 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2017, Halifax, Canada, 13/08/17. https://doi.org/10.1145/3097983.3097985

No longer sleeping with a bomb: A duet system for protecting urban safety from dangerous goods. / Wang, Jingyuan; Chen, Chao; Wu, Junjie et al.
KDD 2017 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery , 2017. p. 1673-1681 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Vol. Part F129685).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - No longer sleeping with a bomb

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AU - Wang, Jingyuan

AU - Chen, Chao

AU - Wu, Junjie

AU - Xiong, Zhang

PY - 2017/8/13

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N2 - Recent years have witnessed the continuous growth of megalopolises worldwide, which makes urban safety a top priority in modern city life. Among various threats, dangerous goods such as gas and hazardous chemicals transported through and around cities have increasingly become the deadly "bomb" we sleep with every day. In both academia and government, tremendous efforts have been dedicated to dealing with dangerous goods transportation (DGT) issues, but further study is still in great need to quantify the problem and explore its intrinsic dynamics in a big data perspective. In this paper, we present a novel system called DGEYE, which features a "duet" between DGT trajectory data and human mobility data for risky zones identification. Moreover, DGEYE innovatively takes risky patterns as the keystones in DGT management, and builds causality networks among them for pain points identification, attribution and prediction. Experiments on both Beijing and Tianjin cities demonstrate the effectiveness of DGEYE. In particular, the report generated by DGEYE driven the Beijing government to lay down gas pipelines for the famous Guijie food street.

AB - Recent years have witnessed the continuous growth of megalopolises worldwide, which makes urban safety a top priority in modern city life. Among various threats, dangerous goods such as gas and hazardous chemicals transported through and around cities have increasingly become the deadly "bomb" we sleep with every day. In both academia and government, tremendous efforts have been dedicated to dealing with dangerous goods transportation (DGT) issues, but further study is still in great need to quantify the problem and explore its intrinsic dynamics in a big data perspective. In this paper, we present a novel system called DGEYE, which features a "duet" between DGT trajectory data and human mobility data for risky zones identification. Moreover, DGEYE innovatively takes risky patterns as the keystones in DGT management, and builds causality networks among them for pain points identification, attribution and prediction. Experiments on both Beijing and Tianjin cities demonstrate the effectiveness of DGEYE. In particular, the report generated by DGEYE driven the Beijing government to lay down gas pipelines for the famous Guijie food street.

KW - Causal analysis

KW - Intelligent transportation

KW - Pattern mining

KW - Urban safety

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T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

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BT - KDD 2017 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

PB - Association for Computing Machinery

Y2 - 13 August 2017 through 17 August 2017

ER -

Wang J, Chen C, Wu J, Xiong Z. No longer sleeping with a bomb: A duet system for protecting urban safety from dangerous goods. In KDD 2017 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery . 2017. p. 1673-1681. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). doi: 10.1145/3097983.3097985

No longer sleeping with a bomb: A duet system for protecting urban safety from dangerous goods

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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