• DocumentCode
    3601367
  • Title

    Urban Resolution: New Metric for Measuring the Quality of Urban Sensing

  • Author

    Liang Liu ; Wangyang Wei ; Dong Zhao ; Huadong Ma

  • Author_Institution
    Beijing Key Lab. of Intell. Telecommun. Software & Multimedia, Beijing Univ. of Posts & Telecommun. Beijing, Beijing, China
  • Volume
    14
  • Issue
    12
  • fYear
    2015
  • Firstpage
    2560
  • Lastpage
    2575
  • Abstract
    The rising popularity of smartphones and vehicles equipped with onboard sensors sheds lights on building a city-scale sensing system for urban surveillance. This paper proposes a novel metric, urban resolution, to measure the quality of urban sensing. Urban resolution describes how sensitivity the urban sensing system could achieve for environment monitoring applications. Then, we study the relationship between resolution r and number of sensing nodes s, and reveal the linear growth relationship between √r and √s . Furthermore, by employing a commonly used human/vehicle mobility model, SLAW, we find that the distribution model of urban sensing nodes is able to be described by a truncated Pareto distribution, and derive the complementary cumulative distribution function (CCDF) of urban resolution. The CCDF reveals the radio of the sub-regions which satisfy the required sensing quality to the whole region. Our findings provide valuable insights to infer the urban sensing quality according to the scale of urban sensing system or determine how many smartphone/vehicles needed for participating in urban sensing applications. Finally, based on five real datasets-three human/vehicle trajectory datasets and two environment monitoring datasets, we examine the metric of urban resolution and evaluate the main results in this paper.
  • Keywords
    Pareto distribution; sensors; smart phones; surveillance; CCDF; SLAW; city-scale sensing system; complementary cumulative distribution function; environment monitoring application; human-vehicle mobility model; human-vehicle trajectory dataset; quality measurement; smartphone; truncated Pareto distribution; urban resolution; urban sensing system; urban surveillance; Cameras; Environmental factors; Image resolution; Intelligent vehicles; Sensor systems; Smart phones; Urban areas; Urban sensing; environment monitoring; mobility model; quality of sensing; resolution;
  • fLanguage
    English
  • Journal_Title
    Mobile Computing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1536-1233
  • Type

    jour

  • DOI
    10.1109/TMC.2015.2404786
  • Filename
    7044580