Portable sensory devices such as sensors equipped mobile phones enable convenient sensing and monitoring of urban areas. Such devices, which are always carried by humans, are referred to as Human Probes. Instead of carrying out sensing activities independently, cooperation of Human Probes helps in realizing efficient urban sensing environments. In this paper, we propose an Architecture of Qualitative Urban Information Blending and Acquisition (Aquiba), in which the sensing activities are adjusted autonomously according to cooperation of Human Probes. Aquiba introduces a cooperative sensing approach which aims to maintain desired sensing resolution efficiently while minimizing overall energy consumption. To study the performance of Aquiba, we have conducted comprehensive simulations ranging from small- to large-scale scenarios along with applying three different movement patterns of human. The simulation results demonstrate that Aquiba is capable of providing high sensing resolution and reducing overall energy consumption.

We present a numerical analysis of the optimal number of active mobile users for minimizing average data delivery delay in intelligent people-centric urban sensing, in which context-aware mobile devices act as sensor-data carriers and sensor nodes act as data accumulators within CDMA cellular networks. In the analysis, we compute the optimal number of mobile users for different environmental conditions and then investigate the minimum average data delivery delay for this optimal number of mobile users.