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AI Architectures for Very Smart Sensors

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Convergence of Artificial Intelligence and the Internet of Things

Part of the book series: Internet of Things ((ITTCC))

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Abstract

The chapter describes modern neural network designs and discusses their advantages and disadvantages. The state-of-the-art neural networks are usually too much computationally difficult which limits their use in mobile and IoT applications. However, they can be modified with special design techniques which would make them suitable for mobile or IoT applications with limited computational power. These techniques for designing more efficient neural networks are described in great detail. Using them opens a way to create extremely efficient neural networks for mobile or even IoT applications. Such neural networks make the applications very intelligent which paves the way for very smart sensors.

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Acknowledgements

This work has been supported by Slovak national project VEGA 2/0155/19.

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  1. Institute of Informatics, Slovak Academy of Sciences, Dúbravská Cesta 9, 845 07, Bratislava, Slovakia

    Peter Malík & Štefan Krištofík

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  1. Peter Malík
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Correspondence to Peter Malík .

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Editors and Affiliations

  1. Department of Management Science and Technology, Hellenic Mediterranean University, Agios Nikolaos, Crete, Greece

    George Mastorakis

  2. Mobile Systems Laboratory (MoSys Lab), Department of Computer Science, Research Centres (UNRF) – University of Nicosia, Nicosia, Cyprus

    Constandinos X. Mavromoustakis

  3. Department of Telecommunications, Warsaw University of Technology, Warsaw, Poland

    Jordi Mongay Batalla

  4. Department of Electrical and Computer Engineering, Hellenic Mediterranean University, Heraklion, Crete, Greece

    Evangelos Pallis

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Malík, P., Krištofík, Š. (2020). AI Architectures for Very Smart Sensors. In: Mastorakis, G., Mavromoustakis, C., Batalla, J., Pallis, E. (eds) Convergence of Artificial Intelligence and the Internet of Things. Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-030-44907-0_16

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