Transportation data visualisation and mining for emergency management

被引:8
|
作者
Lu, Chang-Tien [1 ]
Sripada, Lakshmi N. [1 ]
Shekhar, Shashi [2 ]
Liu, Rulin [2 ]
机构
[1] Virginia Polytech Inst & State Univ, Dept Comp Sci, 7054 Haycock Rd, Falls Church, VA 22043 USA
[2] Univ Minnesota, Dept Comp Sci, Minneapolis, MN 55455 USA
关键词
intelligent transportation system; emergency traffic management; data visualisation; spatial data mining;
D O I
10.1504/IJCIS.2005.006118
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Emergency control systems influence the design, development, and maintenance of public infrastructure in a significant manner. These systems help to restore the infrastructure and sometimes prevent damage in cases of crisis. The road transportation system is an important part of public infrastructure and is one of the critical assets of a nation. Recovering from emergency situations on the road has been one of the major concerns of the traffic management personnel. Many software systems have been developed using advanced technologies to help in the detection of, prevention of and recovery from road crisis. We have developed the CubeView visualisation system based on the concepts of data-visualisation and data mining. Visualisation of loop-detector traffic data can help in the identification of potentially important patterns embedded in the data. CubeView helps in summarising the major trends in traffic patterns for both historical and current data. This paper presents the idea of applying the concepts of data-visualisation and outlier detection to road traffic data using the CubeView system for emergency situation control and management planning. CubeView is a web-based software system and is available at: http://europa.nvc.cs.vt.edu/similar to ctlu/Project/Mapcube/mapcube.htm.
引用
收藏
页码:170 / 194
页数:25
相关论文
共 50 条
  • [31] Mining frequent items and itemsets from distributed data streams for emergency detection and management
    Albino Altomare
    Eugenio Cesario
    Domenico Talia
    Journal of Ambient Intelligence and Humanized Computing, 2017, 8 : 47 - 55
  • [32] The Data Wave: Data Management and Mining
    Kechadi, M-Tahar
    19TH IEEE INTERNATIONAL WORKSHOPS ON ENABLING TECHNOLOGIES: INFRASTRUCTURE FOR COLLABORATIVE ENTERPRISES (WETICE 2010), 2010, : 7 - 11
  • [33] Diagnostic Visualisation of Building Management System Energy Data
    Shabajee, Paul
    Schien, Dan
    Preist, Chris
    Brenton, John
    Jones, Chris
    PROCEEDINGS OF ICT FOR SUSTAINABILITY 2016, 2016, 46 : 233 - 233
  • [34] A Data Science Solution for Mining Weather Data and Transportation Data for Smart Cities
    Nguyen, Ben
    Shinnie, Mark J. D.
    Leung, Carson K.
    Kuzie, Michael R.
    Kokilev, Nikola N.
    Kaur, Sukhmandeep
    2022 IEEE 46TH ANNUAL COMPUTERS, SOFTWARE, AND APPLICATIONS CONFERENCE (COMPSAC 2022), 2022, : 1672 - 1677
  • [35] Design and Implementation of Data Management and Visualisation Module in Financial Digital Management
    Ren, Junying
    JOURNAL OF INFORMATION & KNOWLEDGE MANAGEMENT, 2024,
  • [36] On Intelligent Transportation System Based on GPS and Data Mining
    Yan Bo
    Huang Yehua
    Ma Xinjun
    PROCEEDINGS OF THE 27TH CHINESE CONTROL CONFERENCE, VOL 6, 2008, : 595 - +
  • [37] A transportation guidance system based on data mining and GABP
    Li, Zhuhao
    Guan, Wei
    MECHANICAL DESIGN AND POWER ENGINEERING, PTS 1 AND 2, 2014, 490-491 : 914 - 919
  • [38] Application of Data Mining Technology in Railway Transportation in Era of Big Data
    Luo, Hui
    Zhang, Huang
    Yu, Wenyuan
    NEW INDUSTRIALIZATION AND URBANIZATION DEVELOPMENT ANNUAL CONFERENCE: THE INTERNATIONAL FORUM ON NEW INDUSTRIALIZATION DEVELOPMENT IN BIG-DATA ERA, 2015, : 565 - 569
  • [39] Data Mining for Transportation Mode Recognition from Radio-data
    Zhu, Yida
    Luo, Haiyong
    Guo, Song
    Zhao, Fang
    UBICOMP/ISWC '21 ADJUNCT: PROCEEDINGS OF THE 2021 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING AND PROCEEDINGS OF THE 2021 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS, 2021, : 423 - 427
  • [40] Mining Company Management in Case of the Epidemic Emergency
    Bak, Patrycja
    Kapusta, Mariusz
    Sukiennik, Marta
    INZYNIERIA MINERALNA-JOURNAL OF THE POLISH MINERAL ENGINEERING SOCIETY, 2020, 2 (02): : 231 - 235