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An energy-efficient approach for real-time tracking of moving object in multi-level sensor networks

机译:一种多级传感器网络中实时跟踪运动对象的节能方法

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In this paper, we propose a new approach for efficient and real-time tracking of the moving objects in sensor networks by mining the movement log. In our approach, we first conduct the hierarchical clustering to form a hierarchical model for the sensor nodes. Secondly, the movement logs of the moving objects are analyzed by a data mining algorithm to obtain the movement rules, which are then used to predict the next position of a moving object. Besides, we use the multi-level structure to represent the hierarchical relations among sensors so as to achieve the goal of keeping tracking of moving objects in real-time. Through experimental evaluation on various simulation conditions, the proposed method is shown to deliver excellent performance in terms of both energy efficiency and timeliness.
机译:在本文中,我们提出了一种通过挖掘运动日志来高效,实时地跟踪传感器网络中运动对象的新方法。在我们的方法中,我们首先进行层次聚类,以形成传感器节点的层次模型。其次,通过数据挖掘算法分析运动对象的运动日志,以获得运动规则,然后将其用于预测运动对象的下一个位置。此外,我们使用多层结构来表示传感器之间的层次关系,以达到实时跟踪运动对象的目的。通过在各种仿真条件下的实验评估,所提出的方法在能源效率和及时性方面均表现出出色的性能。

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