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International Conference on Web Engineering

ICWE 2021: ICWE 2021 Workshops pp 27–38Cite as

Towards Proactive Context-Aware IoT Environments by Means of Federated Learning

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1508))

Abstract

Internet of Things (IoT) integrates billions of smart devices and keeps growing. IoT technologies play a crucial role in smart applications that improve the quality of life. Likewise, the computational capacity of mobile devices has greatly increased, opening up new possibilities. In many cases, human interaction is necessary for IoT devices to perform properly. Users must configure more and more devices, investing time and effort. Artificial Intelligence (AI) techniques are currently used to predict user needs and behavior, trying to adapt devices to user preferences. However, achieving all-purpose models is a challenging task, aggravated by long training periods preventing personalized models in the early stages. This paper proposes a solution based on Federated Learning to predict behaviors in different environments and improve user’s coexistence with IoT devices, avoiding most manual interactions and making use of mobile devices capabilities. Federation allows new users’ predictions to be done using other users’ previous behaviors in similar environments. Also, it provides closer customization, immediate availability and avoids most manual device interactions.

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Notes

  1. 1.

    https://www.tensorflow.org/.

  2. 2.

    https://deeplearning4j.org/.

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Acknowledgement

This work was funded by the project RTI2018-094591-B-I00 and the FPU17/02251 grant (MCI /AEI/FEDER, UE), the 4IE+ Project (0499-4IE-PLUS-4-E) funded by the Interreg V-A España-Portugal (POCTEP) 2014–2020 program, by the Department of Economy, Science and Digital Agenda of the Government of Extremadura (GR18112, IB18030), and by the European Regional Development Fund.

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Authors and Affiliations

  1. University of Extremadura, Cáceres, Spain

    Rubén Rentero-Trejo, Daniel Flores-Martin, Jaime Galán-Jiménez, José García-Alonso, Juan Manuel Murillo & Javier Berrocal

Authors
  1. Rubén Rentero-Trejo
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  2. Daniel Flores-Martin
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  3. Jaime Galán-Jiménez
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  4. José García-Alonso
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  5. Juan Manuel Murillo
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  6. Javier Berrocal
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Corresponding author

Correspondence to Rubén Rentero-Trejo .

Editor information

Editors and Affiliations

  1. Novosibirsk State Technical University, Novosibirsk, Russia

    Maxim Bakaev

  2. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    In-Young Ko

  3. InnoRenew CoE, Izola, Slovenia

    Michael Mrissa

  4. Universita della Svizzera Italiana, Lugano, Switzerland

    Cesare Pautasso

  5. Indian Institute of Technology Indore, Indore, India

    Abhishek Srivastava

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Rentero-Trejo, R., Flores-Martin, D., Galán-Jiménez, J., García-Alonso, J., Murillo, J.M., Berrocal, J. (2022). Towards Proactive Context-Aware IoT Environments by Means of Federated Learning. In: Bakaev, M., Ko, IY., Mrissa, M., Pautasso, C., Srivastava, A. (eds) ICWE 2021 Workshops. ICWE 2021. Communications in Computer and Information Science, vol 1508. Springer, Cham. https://doi.org/10.1007/978-3-030-92231-3_3

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  • DOI: https://doi.org/10.1007/978-3-030-92231-3_3

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  • Print ISBN: 978-3-030-92230-6

  • Online ISBN: 978-3-030-92231-3

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