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Automated and Optimized Sensor Deployment using Building Models and Electromagnetic Simulation

机译:使用构建模型和电磁仿真来自动化和优化传感器部署

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摘要

With the advent of wireless sensing technology and interest in tracking resources, researchers have developed advanced tracking algorithms by using one or more sensor systems for improved accuracy and reliability of tracking. The objective of this research lies in another aspect-deployment-of tracking that has received only little attention until now. The research explores a method for sensor deployment particularly designed for the building in which the sensors are used. To tailor our solution to a specific building, we integrate a building information model with an electromagnetic energy analysis. By using such a model, the system extracts the properties of building materials, which are used as parameters of sensor deployment optimization. Then, we find a method of optimizing the deployment of a Received Signal Strength Indication (RSSI)-based tracking sensors for reducing wireless energy dissipation during the operation of the tracking system. For the numerical validation of the proposed method, the High-Frequency Structural Simulator (HFSS) runs an electromagnetic simulation to generate comparison data of electromagnetic energy flow from optimized sensor deployment and random sensor deployment. The results indicate that the proposed method could produce results that are correlated to the HFSS results. In addition, the method shows clear evidence of a reduction in signal power loss. Finally, optimized sensor deployment through the proposed framework can use signals of electromagnetic energy more effectively and potentially improve the efficiency of the RSSI-based tracking system.
机译:随着无线传感技术的出现和对跟踪资源的兴趣,研究人员通过使用一个或多个传感器系统开发了先进的跟踪算法,以提高跟踪的准确性和可靠性。这项研究的目的在于进行跟踪的另一个方面-部署-到目前为止,仅受到很少的关注。该研究探索了一种传感器部署方法,该方法专门针对使用传感器的建筑物而设计。为了针对特定建筑物量身定制解决方案,我们将建筑物信息模型与电磁能分析相集成。通过使用这样的模型,系统提取建筑材料的属性,这些属性用作传感器部署优化的参数。然后,我们找到一种优化基于接收信号强度指示(RSSI)的跟踪传感器的部署的方法,以减少跟踪系统运行过程中的无线能耗。为了对所提出方法进行数值验证,高频结构模拟器(HFSS)进行了电磁仿真,以从优化的传感器部署和随机传感器部署中生成电磁能流的比较数据。结果表明,该方法可以产生与HFSS结果相关的结果。另外,该方法显示出信号功率损耗降低的明显证据。最后,通过提出的框架优化的传感器部署可以更有效地利用电磁能信号,并有可能提高基于RSSI的跟踪系统的效率。

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