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Multi-sensor fusion based intelligent sensor relocation for health and safety monitoring in BSNs

机译:基于多传感器融合的BSNS健康安全监控智能传感器搬迁

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摘要

The body sensor networks (BSNs) have attracted great attention due to their numerous important features and wide applications in health and safety monitoring, especially in some hostile or potentially dangerous workplaces. In this paper, aiming to provide continuous coverage from the initial Region of Interest (ROI) to a New Region of Interest (NROI) to trace the BSNs for human health and safety monitoring, we formulate and define the novel confident information coverage (CIC)-based Intelligent Sensor Relocation for NROI (CIC-ISR-NROI) problem in mobile wireless sensor networks (MWSNs) based on the novel CIC model. For handing the CIC-ISR-NROI problem, we develop two energy-efficient intelligent sensor relocation algorithms based on multi-sensor fusion, the Rapid Relocation Time Low Energy Consumption (RRTLEC) algorithm and optimized RRTLEC algorithm, to relocate redundant mobile sensors from the ROI to cover the NROI in a timely and energy-efficient manner while constructing the communication chain to connect the ROI and the NROI. To verify the effectiveness and efficiency of the proposed schemes, we conduct a series of experiments which correspond to the realistic scenarios in health and safety monitoring in the 272 uranium tailing. Experimental results show that the performance of our approaches is better than the other typical peer approaches by the metrics of the total moving energy consumption and the maximum relocation time.
机译:由于其许多重要的特征和健康和安全监测中的广泛应用,尤其是在一些敌对或潜在的危险工作场所,因此身体传感器网络(BSNS)引起了极大的关注。在本文中,旨在提供从初始感兴趣区域(ROI)到新的兴趣区域(NROI)的持续覆盖,以追踪人类健康和安全监测的BSN,我们制定和定义新的信心信息覆盖(CIC)基于新型CIC模型的移动无线传感器网络(MWSNS)中的NROI(CIC-ISR-NROI)问题的基于智能传感器重定位。为了递送CIC-ISR-NROI问题,我们开发了基于多传感器融合的两个节能智能传感器重定位算法,快速重定位时间低能量消耗(RRTLEC)算法和优化的RRTLEC算法,从而重新定位冗余移动传感器ROI以及时和节能的方式覆盖NROI,同时构建通信链以连接ROI和NROI。为了验证提出的计划的有效性和效率,我们进行了一系列实验,该实验对应于272铀尾矿中的健康和安全监测的现实情景。实验结果表明,我们的方法的性能优于总移动能耗和最大重定位时间的指标优于其他典型的对等方法。

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