A Simulation Study of Human-Probe Approach for Urban Sensing

Portable sensory devices carried by humans-which are referred to as Human Probes-facilitate easy-to-use sensing and monitoring of urban areas. However, when each Human Probe individually senses and transmits information, the sensing is inefficient in terms of energy consumption. In this paper, we propose an architecture called Architecture of QUality-enhanced Information Blending and Aggregation (Aquiba), in which the sensing activities carried out by the Human Probes adaptively adjust under different conditions. Aquiba involves cooperative sensing that help in efficiently maintaining the desired sensing resolution while minimizing energy consumption. We study the performance of Aquiba by running simulations in which large-scale scenarios are considered along with a realistic movement pattern of Human Probes. The simulation results demonstrate that cooperative sensing is capable of providing the desired sensing resolution and reducing energy consumption.