A virtual layer of measure based on soft sensors

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• 作者：Umberto Maniscalco ; Riccardo Rizzo
• 关键词：Soft sensors ; Virtual measurement ; Neural networks ; Environmental monitoring
• 刊名：Journal of Ambient Intelligence and Humanized Computing
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：8
• 期：1
• 页码：69-78
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Computational Intelligence; Artificial Intelligence (incl. Robotics); Robotics and Automation; User Interfaces and Human Computer Interaction;
• 出版者：Springer Berlin Heidelberg
• ISSN：1868-5145
• 卷排序：8

文摘

In this paper it is proposed a method to design and train a layer of soft sensors based on neural networks in order to constitute a virtual layer of measure in a wireless sensor network. Each soft sensor of the layer esteems the missing values of some hardware sensors by using the values obtained from some other sensors. In so doing, we perform a spatial forecasting. The correlation analysis for all parameter taken into account is used to define a cluster of real sensors used as sources of measure to esteem missing values. An application concerning the fire prevention field is used as a test case and results evaluation.