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Embedding a Neural Network into WSN furniture

机译:将神经网络嵌入到WSN家具中

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Wireless Sensor Networks (WSN) is an emerging technology that is developed with a large number of useful applications. On the other hand, Artificial Neural Networks (ANN) have found many successful applications in nonlinear system and control, digital communication, pattern recognition, pattern classification, etc. There are many similarities between WSN and ANN. For example, the sensor node itself can be seen as a neuron since the WSN application show characteristics such as distributed processing, massive parallelism, adaptively, inherent contextual information processing, fault tolerance and low computation. This paper examines the possibility of embedding ANN and WSN into a Smart Table. Prototypal results have shown that ANN models are good candidates for using it deployed into low cost System-on-a-Chip (SoC).
机译:无线传感器网络(WSN)是一种具有大量有用应用程序开发的新兴技术。另一方面,人工神经网络(ANN)在非线性系统和控制,数字通信,模式识别,模式分类等中找到了许多成功的应用。WSN和ANN之间存在许多相似之处。例如,传感器节点本身可以​​被视为神经元,因为WSN应用示出了诸如分布式处理,大规模并行性,自适应,固有的上下文信息处理,容错和低计算的特征。本文审查了将ANN和WSN嵌入到智能桌中的可能性。原型结果表明,ANN模型是使用部署成低成本系统(SOC)的良好候选者。

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