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A fuzzy decision based WSN localization algorithm for wise healthcare

机译:基于模糊决策的WSN智能医疗定位算法

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Wise healthcare is a typical application of wireless sensor network (WSN), which uses sensors to monitor the physiological state of nursing targets and locate their position in case of an emergency situation. The location of targets need to be determined and reported to the control center, and this leads to the localization problem. While localization in healthcare field demands high accuracy and regional adaptability, the information processing mechanism of human thinking has been introduced, which includes knowledge accumulation, knowledge fusion and knowledge expansion. Furthermore, a fuzzy decision based localization approach is proposed. Received signal strength (RSS) at references points are obtained and processed as position relationship indicators, using fuzzy set theory in the knowledge accumulation stage; after that, optimize degree of membership corresponding to each anchor nodes in different environments during knowledge fusion; the matching degree of reference points is further calculated and sorted in decision-making, and the coordinates of several points with the highest matching degree are utilized to estimate the location of unknown nodes while knowledge expansion. Simulation results show that the proposed algorithm get better accuracy performance compared to several traditional algorithms under different typical occasions.
机译:明智的医疗保健是无线传感器网络(WSN)的典型应用,该网络使用传感器监视护理对象的生理状态并在紧急情况下定位他们的位置。需要确定目标的位置并报告给控制中心,这会导致定位问题。虽然医疗领域的本地化要求较高的准确性和区域适应性,但已经引入了人类思维的信息处理机制,包括知识积累,知识融合和知识扩展。此外,提出了一种基于模糊决策的定位方法。在知识积累阶段,采用模糊集理论,获取参考点的接收信号强度(RSS)并作为位置关系指标进行处理;然后,在知识融合过程中,优化不同环境中各个锚节点对应的隶属度。参考点的匹配度在决策中进一步计算和排序,在知识扩展的同时,利用匹配度最高的几个点的坐标估计未知节点的位置。仿真结果表明,与几种传统算法在不同典型情况下相比,该算法具有更好的精度。

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