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Applications of Computational Intelligence in Industrial and Environmental Scenarios

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Learning Systems: From Theory to Practice

Part of the book series: Studies in Computational Intelligence ((SCI,volume 756))

Abstract

Computational Intelligence (CI) techniques are receiving increasing attention by the industrial and academic communities involved in the design of automatic systems for industrial and environmental monitoring and control applications. CI techniques are able to aggregate inputs from several heterogeneous sensors, adapt themselves to wide ranges of operational and environmental conditions, and cope with incomplete or noise-affected data. With current computing architectures evolving towards smaller size, higher computational power, and more affordable cost, a great number of devices can embed CI techniques to support different kinds of applications. In this paper, we present a survey of the recent CI methods designed for the main processing steps of industrial and environmental monitoring systems.

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Acknowledgements

This work was supported in part by the EC within the H2020 program under grant agreement 644597 (ESCUDO-CLOUD).

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Authors and Affiliations

  1. Department of Computer Science, Università Degli Studi di Milano, via Bramante 65, 26013, Crema, Italy

    Ruggero Donida Labati, Angelo Genovese, Enrique Muñoz, Vincenzo Piuri & Fabio Scotti

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  1. Ruggero Donida Labati
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  2. Angelo Genovese
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  3. Enrique Muñoz
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  4. Vincenzo Piuri
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Correspondence to Ruggero Donida Labati .

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  1. Bulgarian Academy of Sciences, Institute of Information and Communication Technology, Sofia, Bulgaria

    Vassil Sgurev

  2. Department of Computer Science, Università degli Studi di Milano, Crema, Italy

    Vincenzo Piuri

  3. University of Library Studies and Information Technologies, Sofia, Bulgaria

    Vladimir Jotsov

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Donida Labati, R., Genovese, A., Muñoz, E., Piuri, V., Scotti, F. (2018). Applications of Computational Intelligence in Industrial and Environmental Scenarios. In: Sgurev, V., Piuri, V., Jotsov, V. (eds) Learning Systems: From Theory to Practice. Studies in Computational Intelligence, vol 756. Springer, Cham. https://doi.org/10.1007/978-3-319-75181-8_2

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