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Rope Deployment Method for Ropeway-Type Vermin Detection Systems

机译:索道式害虫检测系统的绳索展开方法

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In recent years, damage to rural areas by vermin such as deer, wild boars or monkeys has increased in both frequency and severity. This problem is expected to be counteracted by wireless sensor networks constructed from multiple sensor nodes with wireless communication devices. These systems reduce the damage by detecting vermin and repelling them by signals such as sounds and light. However, owing to their fixed monitoring cameras, general monitoring systems cannot always cope with plant growth and other obscurations that decrease the monitored area. This paper proposes a ropeway-type vermin detection system that moves the monitoring cameras on ropes, and a method that minimizes the number of required ropes in the expected monitoring scenario. For efficient monitoring with as few cameras as possible, the method groups several target areas into one by a clustering procedure. The grouped area can then be monitored from a single position. Subsequently, our algorithm finds the most efficient rope deployment that completely monitors the grouped areas. In simulations, the proposed method monitored all target areas with 26% fewer monitoring cameras than a general clustering method (k-means clustering).
机译:近年来,诸如鹿,野猪或猴子等害虫对农村地区的破坏频率和严重性都增加了。预期该问题将由由具有无线通信设备的多个传感器节点构成的无线传感器网络来解决。这些系统通过检测害虫并通过声音和光等信号来驱除害虫,从而减少了损害。但是,由于固定的监控摄像机,一般的监控系统无法始终应对植物生长以及其他减少监控区域的遮盖物。本文提出了一种可在绳索上移动监控摄像机的索道式害虫检测系统,以及一种在预期的监控方案中将所需绳索数量最小化的方法。为了用尽可能少的摄像机进行有效监视,该方法通过聚类过程将多个目标区域分组为一个区域。然后可以从单个位置监视分组区域。随后,我们的算法找到了最有效的绳索部署,该绳索部署可以完全监视分组区域。在仿真中,与常规聚类方法(k均值聚类)相比,所提出的方法以少于26%的监视摄像机监视所有目标区域。

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