作者: Sara Hachem , Vivien Mallet , Raphael Ventura , Animesh Pathak , Valerie Issarny
DOI: 10.1109/BIGDATASERVICE.2015.16
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摘要: Noise pollution is a significant problem in cities due to its various effects on health, but the modeling of noise data and generation accurate maps suffer from high cost restricted scale sensing performed using static municipal sensors. In this paper, we present our approach for augmenting municipally sensed participatory sensing-based information collected smart phones. We make use assimilation method generate more that combine simulated measured levels. Our solution customizes Urban Civics middleware noise-specific application. combines solutions urban-scale crowd-sourcing, techniques, which are main focus generate, collect, process big involved scalable manner. experiments demonstrate improvements quality enabled by technique vis-a-vis map usually generated with simulation along observational alone or mobile alone.