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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Bibliographic Details
Published in:Journal of ambient intelligence and humanized computing 2017-02, Vol.8 (1), p.69-78
Main Authors: Maniscalco, Umberto, Rizzo, Riccardo
Format: Article
Language:English
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
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Summary: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.
ISSN:1868-5137
1868-5145
DOI:10.1007/s12652-016-0350-y