Optimal Deployment of Dense WSN for Error Bounded Air Pollution Mapping

Ahmed Boubrima, Walid Bechkit, H. Rivano
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引用次数: 7

Abstract

Air pollution has become a major issue of modern megalopolis because of industrial emissions and increasing urbanization along with traffic jams and heating/cooling of buildings. Monitoring urban air quality is therefore required by municipalities and by the civil society. Current monitoring systems rely on reference sensing stations that are precise but massive, costly and therefore seldom. In this ongoing work, we focus on an alternative or complementary approach, using a network of low cost and autonomic wireless sensors, allowing for a finer spatiotemporal granularity of air quality sensing. We tackle the optimization problem of sensor deployment and propose an integer programming model, which allows to find the optimal network topology while ensuring air quality monitoring with a high precision and the minimum financial cost. Most of existing deployment models of wireless sensor networks are generic and assume that sensors have a given detection range. This assumption does not fit pollutant concentrations sensing. Our model takes into account interpolation methods to place sensors in such a way that pollution concentration is estimated with a bounded error at locations where no sensor is deployed.
基于误差有界空气污染映射的密集WSN优化部署
空气污染已经成为现代大城市的一个主要问题,因为工业排放和日益增长的城市化以及交通堵塞和建筑物的供暖/制冷。因此,市政当局和民间社会都需要监测城市空气质量。目前的监测系统依赖于参考传感站,这些站点虽然精确,但体积庞大,成本高昂,因此很少使用。在这项正在进行的工作中,我们专注于一种替代或补充方法,使用低成本和自主无线传感器网络,允许更精细的空气质量时空粒度传感。我们解决了传感器部署的优化问题,并提出了一个整数规划模型,该模型可以找到最优的网络拓扑,同时确保空气质量监测具有高精度和最小的财务成本。大多数现有的无线传感器网络部署模型都是通用的,并且假设传感器具有给定的检测范围。这一假设不适合污染物浓度传感。我们的模型考虑了插值方法,以这样一种方式放置传感器,在没有部署传感器的位置以有界误差估计污染浓度。
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