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UAV-aided Weak-Barrier Coverage with Adaptive Sensor Rotation

机译:具有自适应传感器旋转的无人机辅助弱势屏障覆盖

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Unmanned Aerial Vehicles (UAVs) is an emerging technology with many applications in surveillance, remote sensing, transportation, scientific research, search and rescue, and many more. In wireless sensor networks, UAVs have been used as mobile sinks and as relay nodes when the network is partitioned. When deploying sensors to monitor large boundaries or borders, sensors are usually dispersed from an aircraft following a predetermined path. In such scenarios sensing gaps are typically unavoidable. In this paper, we consider a wireless network consisting of randomly deployed sensor nodes, directional border nodes, and an UAV. We address the topic of weak-barrier coverage, which detects intruders (or events) moving north-south. We propose a distributed algorithm for weak-barrier coverage, that allows border nodes to dynamically compute their orientation based on notifications from sensor nodes. The UAV is used to monitor barrier gaps and increase the number of intruders detected when crossing the border. We use simulations using MatLab to analyze the performance of our algorithm, and to illustrate the impact of using an UAV in monitoring, when we vary various parameters such as the number of nodes, the view angle of the border nodes, and the event speed.
机译:无人驾驶飞行器(UAV)是在监视许多应用,遥感,交通,科研,搜索和救援,以及更多的新兴技术。在无线传感器网络中,在网络分区时,UAV已被用作移动宿和作为中继节点。在部署传感器以监视大边界或边界时,传感器通常在预定路径之后的飞机上分散。在这种情况下,传感间隙通常是不可避免的。在本文中,我们考虑由随机部署的传感器节点,方向边界节点和UAV组成的无线网络。我们解决了弱势障碍覆盖的主题,可检测移动南北移动的入侵者(或事件)。我们提出了一种用于弱势屏障覆盖的分布式算法,允许边界节点基于来自传感器节点的通知动态计算它们的方向。 UAV用于监控屏障间隙并增加交叉边界时检测到的入侵者的数量。我们使用MATLAB使用模拟来分析我们的算法的性能,并说明在不同的参数,边界节点的视角和事件速度等各种参数,以及事件速度等各种参数时,使用无人机在监控中的影响。

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