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HCTTR: A complete scheme for object tracking and recovery of lost objects in cluster-based wireless sensor networks

机译:HCTT&R:用于基于集群的无线传感器网络中的对象跟踪和丢失对象恢复的完整方案

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摘要

This paper takes a look at the performance of an energy-efficient object tracking wireless sensor network. As you know object tracking is vulnerable to object losing due to reasons like predicting errors, sensor failures and abrupt changes in speed/course of the object. For a reliable object tracking method that could be used in critical situations, a foolproof mechanism is needed. This paper examines a novel object tracking method (HCTT&R) to track objects and recover lost objects in a clustered network. The simulation has been carried out using the Castalia simulation framework of OMNET++ to compare the proposed method with the base method to show the benefits and defeats of the proposed method. Finally with transferring the acquired data from Castalia into Matlab and interpolating them (LOWESS algorithm), we find a smooth course of object which let the user decide more easily about the future actions of the tracked object(s).
机译:本文着眼于节能对象跟踪无线传感器网络的性能。如您所知,由于诸如预测错误,传感器故障和物体速度/航向的突然变化等原因,物体跟踪很容易造成物体丢失。对于可以在紧急情况下使用的可靠的对象跟踪方法,需要一种万无一失的机制。本文研究了一种新颖的对象跟踪方法(HCTT&R),用于在群集网络中跟踪对象并恢复丢失的对象。该仿真是使用OMNET ++的Castalia仿真框架进行的,以将所提出的方法与基本方法进行比较,以显示所提出方法的优缺点。最后,将所采集的数据从Castalia传输到Matlab并进行插值(LOWESS算法),我们发现了对象的平滑过程,这使用户可以更轻松地决定所跟踪对象的未来动作。

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