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A Method to Construct an Indoor Air Pollution Monitoring System Based on a Wireless Sensor Network

机译:基于无线传感器网络的室内空气污染监测系统的构建方法

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摘要

Wireless Sensors Networks (WSNs) are currently receiving much research interest due to their wide-ranging use is a number of different fields. In the current study, a system based on a WSN is proposed that can monitor indoor air pollution in several public spaces, such as subway stations, offices, schools, and hospitals. The proposed system uses integrated sensors in mobile phones, moving from a stationary nodes model to a mobile nodes model. The main objective of building this system is to provide full coverage of the target area. To achieve this goal, the system is simulated by MATLAB and the following algorithms are applied: Particle Swarm Optimization (PSO) to maximize the coverage in the region of interest (RoI), Voronoi Diagram (VD) to detect holes in the coverage, and finally the Point in Polygon (PiP) algorithm to heal the holes in the coverage. The application of the algorithms mentioned above has been very effective as PSO has increased the coverage rate of the monitoring area to 100%. The VD allowed us to define the exact location of coverage holes whilew the Point in Polygon algorithm allowed us to heal the holes and find the remaining sensors in order to improve network coverage. This enabled us to achieve full coverage of the monitoring area.
机译:无线传感器网络(WSN)由于在许多不同领域中的广泛使用而受到了广泛的研究兴趣。在当前的研究中,提出了一种基于WSN的系统,该系统可以监视地铁,办公室,学校和医院等多个公共场所的室内空气污染。拟议的系统在移动电话中使用集成传感器,从固定节点模型转移到移动节点模型。构建此系统的主要目的是提供目标区域的完整覆盖。为实现此目标,系统通过MATLAB进行了仿真,并应用了以下算法:粒子群优化(PSO)以最大化感兴趣区域(RoI)的覆盖范围,沃罗诺伊图(VD)以检测覆盖范围内的空洞,以及最后使用多边形中的点(PiP)算法修复覆盖中的孔。由于PSO已将监视区域的覆盖率提高到100%,因此上述算法的应用非常有效。 VD允许我们定义覆盖孔的确切位置,而“多边形中的点”算法则允许我们修复孔并找到剩余的传感器以改善网络覆盖范围。这使我们能够完全覆盖监视区域。

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