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Real-Time Sensor Fusion Framework for Distributed Intelligent Sensors

机译:分布式智能传感器的实时传感器融合框架

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摘要

Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor fusion framework (RTSFF) based on distributed intelligent sensor network. The RTSFF is an open architecture which consists of four layers - the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The transducer layer is populated with intelligent sensors. The learning ability of the intelligent sensor model enables it to extract characteristics of monitored signal. The representation issue is managed at this level. After describing the RTSFF, the paper then focuses on the fundamental units of the framework, the highly autonomous transducers.
机译:多传感器数据融合已在工业和研究领域中得到了广泛的应用。实时多传感器数据融合的目的是从一组不同的数据源(即传感器)动态估计改进的系统模型。本文提出了一种基于分布式智能传感器网络的系统,统一的实时传感器融合框架(RTSFF)。 RTSFF是一种开放式体系结构,由四层组成-事务层,流程融合层,控制层和计划层。这种范例有助于将智能分配到传感器级别,并在系统中的传感器,控制器和其他设备之间共享信息。换能器层装有智能传感器。智能传感器模型的学习能力使其能够提取监视信号的特征。表示问题在此级别进行管理。在描述了RTSFF之后,本文将重点介绍框架的基本单元,即高度自主的传感器。

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