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COEVRAGE ESTIMATION OF GEOSENSOR IN 3D VECTOR ENVIRONMENTS

机译:3D矢量环境中生物传感器的覆盖范围

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Sensor deployment optimization to achieve the maximum spatial coverage is one of the main issues in Wireless geoSensor Networks (WSN). The model of the environment is an imperative parameter that influences the accuracy of geosensor coverage. In most of recent studies, the environment has been modeled by Digital Surface Model (DSM). However, the advances in technology to collect 3D vector data at different levels, especially in urban models can enhance the quality of geosensor deployment in order to achieve more accurate coverage estimations. This paper proposes an approach to calculate the geosensor coverage in 3D vector environments. The approach is applied on some case studies and compared with DSM based methods.
机译:传感器部署优化以实现最大空间覆盖率是无线地球传感器网络(WSN)中的主要问题之一。环境模型是一种势在必行的参数,影响大浮位体覆盖的准确性。在最近的大部分研究中,环境已经通过数字表面模型(DSM)进行了建模。然而,技术在不同层次中收集3D矢量数据的进步,特别是在城市模型中可以提高地磁体验部署的质量,以实现更准确的覆盖估计。本文提出了一种方法来计算3D传染媒介环境中的地磁体覆盖范围。该方法适用于某种案例研究,并与基于DSM的方法进行比较。

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