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 $\sqrt{r}$ and $\sqrt{s}$ . 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.
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