Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/1719970.1720030acmconferencesArticle/Chapter ViewAbstractPublication PagesiuiConference Proceedingsconference-collections
poster

Ocean of information: fusing aggregate & individual dynamics for metropolitan analysis

Published: 07 February 2010 Publication History

Abstract

In this paper, we propose a tool to explore human movement dynamics in a Metropolitan Area. By analyzing a mass of individual cell phone traces, we build a Human-City Interaction System for understanding urban mobility patterns at different user-controlled temporal and geographic scales. We solve the problems that are found in available tools for spatio-temporal analysis, by allowing seamless manipulability and introducing a simultaneous\multi-scale visualization of individual and aggregate flows. Our tool is built to support the exploration and discovery of urban mobility patterns and the daily interactions of millions of people. Moreover, we implement an intelligent algorithm to evaluate the level of mobility homophily of people moving from place to place.

Supplementary Material

JPG File (p357-martino.jpg)
MOV File (p357-martino.mov)

References

[1]
González, M. C., Hidalgo, C. A., and Barabási, A. L. (2008). Understanding individual human mobility patterns. Nature 453, pp. 779--782.
[2]
D.Norman. Emotional Design: Why we love (or hate) everyday things. Basic Books, 2004
[3]
J. Reades, F. Calabrese, A. Sevtsuk, and C. Ratti. Cellular census: Explorations in urban data collection. IEEE Pervasive Computing Magazine, 6(3):30--38, 2007. Hancock, J. T., Toma, C., and Ellison, N. (2007). The truth about lying in online dating profiles. CHI 2007. ACM, New York, NY.
[4]
Orange Labs and Faber Nove. UrbanMobs, http://www.fabernovel.com, Revised in 30 August 2009.
[5]
Z. Shen, K. Ma. MobiVis -- A Visualization System for Exploring Mobile Data. Visualization & Interface Design Innovation (VIDi), 2007.
[6]
T. Wang, B. Yang, J. Gao. MobileMiner: A Real World Case Study of Data Mining in Mobile Communication. SIGMOD 2009.
[7]
T. Kapler and W. Wright. GeoTime Information Visualization. InfoVis 2004.
[8]
J.A. Dykes, "Exploring spatial data representation with dynamic graphics", Computers and Geosciences 23 (4), pp. 345--370, 1997.
[9]
Tufte, E., Envisioning Information, Graphics Press, Cheshire, CT, 1990.
[10]
Reades J, Calabrese F, Ratti C, 2009, "Eigenplaces: analysing cities using the space - time structure of the mobile phone network" Environment and Planning B: Planning and Design 36(5) 824 -- 836
[11]
P. Wang, M.C. González, C.A. Hidalgo and A.- L.Barabási Understanding the spreading patterns of mobile phones viruses, Science 324, 1071--1076 (2009).

Cited By

View all

Index Terms

  1. Ocean of information: fusing aggregate & individual dynamics for metropolitan analysis

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    IUI '10: Proceedings of the 15th international conference on Intelligent user interfaces
    February 2010
    460 pages
    ISBN:9781605585154
    DOI:10.1145/1719970
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 07 February 2010

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. cellphone data analysi
    2. exploratory spatial data analysis
    3. graph visualization
    4. intelligent human information interaction
    5. visual analysis

    Qualifiers

    • Poster

    Conference

    IUI '10
    Sponsor:

    Acceptance Rates

    Overall Acceptance Rate 746 of 2,811 submissions, 27%

    Upcoming Conference

    IUI '25

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)5
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 10 Oct 2024

    Other Metrics

    Citations

    Cited By

    View all
    • (2015)Mobile Phones as Ubiquitous Social and Environmental Geo-SensorsEncyclopedia of Mobile Phone Behavior10.4018/978-1-4666-8239-9.ch098(1194-1213)Online publication date: 2015
    • (2015)A survey of results on mobile phone datasets analysisEPJ Data Science10.1140/epjds/s13688-015-0046-04:1Online publication date: 5-Aug-2015
    • (2015)Data from mobile phone operatorsTelecommunications Policy10.1016/j.telpol.2014.04.00139:3(335-346)Online publication date: 1-May-2015
    • (2014)AllAboardProceedings of the 19th international conference on Intelligent User Interfaces10.1145/2557500.2557532(335-340)Online publication date: 24-Feb-2014
    • (2014)From Sensing to Action: Quick and Reliable Access to Information in Cities Vulnerable to Heavy RainIEEE Sensors Journal10.1109/JSEN.2014.235498014:12(4175-4184)Online publication date: Dec-2014
    • (2013)Data from telecommunication networks for incident management: An exploratory review on transport safety and securityTransport Policy10.1016/j.tranpol.2012.08.00628(86-102)Online publication date: Jul-2013
    • (2012)Geosensor Data Representation Using Layered Slope GridsSensors10.3390/s12121707412:12(17074-17093)Online publication date: 12-Dec-2012
    • (2012)A Visual Analytics Approach for Extracting Spatio-Temporal Urban Mobility Information from Mobile Network TrafficISPRS International Journal of Geo-Information10.3390/ijgi10302561:3(256-271)Online publication date: 2-Nov-2012
    • (2012)Inferring human mobility patterns from anonymized mobile communication usageProceedings of the 10th International Conference on Advances in Mobile Computing & Multimedia10.1145/2428955.2428988(151-160)Online publication date: 3-Dec-2012

    View Options

    Get Access

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media