Target tracking in face track with Kalman filter using wireless sensor network and development of courier management service in Face Track network

Suvidha D. Dhore, S. Patil
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引用次数: 1

Abstract

Technology of wireless sensor communication has revolutionized our way of living motivated in development and improvement in the field of wireless sensor network. Among many applications target tracking application requires sensor nodes to be localized with minor error. To maintain the target tracking in timely fashion with accurate measurement of target movement is difficult as it summed up with many noises during the detection. Possibilities of node failure often come across in the tracking which results in loss of tracking. Thus to overcome difficulties of tracking new improved tracking framework called as Face (Polygons) Track is proposed. In Face Track sensors are deployed in polygonal fashion. Where polygon share common edge with non overlapping pattern these polygons are the faces and edges being reconstructed to generate each face further so as to avoid loss of tracking. In Face track with Kalman filter, KF optimally selects node as target moves ahead crossing the edges of the face. The Face track network is mapped to develop the courier management system. In this courier management, optimal node selection function selects the number of nodes between source and destination on basis of distance calculated between these node so as to refer nearest node.
基于无线传感器网络的卡尔曼滤波人脸跟踪目标跟踪以及人脸跟踪网络快递管理服务的开发
无线传感器通信技术彻底改变了我们的生活方式,推动了无线传感器网络领域的发展和完善。在许多应用中,目标跟踪应用要求传感器节点的定位误差很小。由于检测过程中存在大量的噪声,要保持目标的及时跟踪并准确测量目标的运动是很困难的。在跟踪过程中经常会遇到节点故障的可能性,从而导致跟踪丢失。为了克服跟踪困难,提出了一种改进的人脸(多边形)跟踪框架。在人脸跟踪传感器部署在多边形的方式。当多边形与非重叠的图案有共同的边时,这些多边形就是要重构的面和边,从而进一步生成每个面,以避免丢失跟踪。在卡尔曼滤波的人脸跟踪中,KF在目标穿过人脸边缘时最优地选择节点。对人脸轨迹网络进行映射,开发快递管理系统。在快递管理中,最优节点选择函数根据计算出的出发地与目的地之间的距离,选择出发地与目的地之间的节点数量,以参考最近的节点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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