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A virtual layer of measure based on soft sensors
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 fr...
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Published in: | Journal of ambient intelligence and humanized computing 2017-02, Vol.8 (1), p.69-78 |
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container_title | Journal of ambient intelligence and humanized computing |
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creator | Maniscalco, Umberto Rizzo, Riccardo |
description | 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. |
doi_str_mv | 10.1007/s12652-016-0350-y |
format | article |
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subjects | Artificial Intelligence Computational Intelligence Correlation analysis Engineering Fire prevention Neighborhoods Neural networks Neurons Original Research Robotics and Automation Saturn Sensors Software User Interfaces and Human Computer Interaction Wireless sensor networks |
title | A virtual layer of measure based on soft sensors |
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