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Evolutionary and Adaptive Elderly Care Ecosystem

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Computational Science and Its Applications – ICCSA 2019 (ICCSA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11623))

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Abstract

Personalized care services for each individual are typically required in the aging process. Considering this domain, a collaborative elderly care ecosystem (ECE) is proposed to support the provision of composite services that may combine contributions from multiple service providers. A personalized solution is built through of services composition, tailored to the individual customer (senior), respecting her/his requirements, preferences, lifestyle, and constraints. An additional issue the ecosystem must deal with is the problem of evolution, as individual’s care needs are not static over time. Consequently, the care services need to evolve accordingly to keep the elderly’s requirements satisfied. This process of services’ adaptation is challenging since many services can be dependent on each other, and there are various constraints that need to be observed before adaptating and enacting new services. In this paper, we exploit socio-technical aspects of service adaptation in the context of elderly care ecosystems. Starting with a service personalization method previously proposed (SCoPE method), we presented an adaptive and evolutionary system (SEvol) based on the MAPE-K methodology. The SEvol method considers customer’s inputs and suggests evolution plans. In the end, a workflow diagram is presented considering the main processes of ECE demonstrating the roles of the ECE environments and the main stakeholders, according to three stages: preparation, execution and monitoring phase.

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Acknowledgements

The authors acknowledge the contributions of the Portuguese FCT-Strategic program UID/EEA/00066/2019 for providing partial financial support for this work.

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Authors and Affiliations

  1. Faculty of Science and Technology and UNINOVA-CTS, NOVA University of Lisbon, Campus de Caparica, 2829-516, Caparica, Portugal

    Thais A. Baldissera & Luis M. Camarinha-Matos

  2. Instituto Federal Farroupilha, Santa Maria, RS, 97050-685, Brazil

    Thais A. Baldissera

Authors
  1. Thais A. Baldissera
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  2. Luis M. Camarinha-Matos
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Corresponding author

Correspondence to Thais A. Baldissera .

Editor information

Editors and Affiliations

  1. Covenant University, Ota, Nigeria

    Sanjay Misra

  2. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  3. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Saint Petersburg State University, Saint Petersburg , Russia

    Vladimir Korkhov

  6. Polytechnic University of Bari, Bari, Italy

    Carmelo Torre

  7. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  8. Monash University, Clayton, VIC, Australia

    David Taniar

  9. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  10. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

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Baldissera, T.A., Camarinha-Matos, L.M. (2019). Evolutionary and Adaptive Elderly Care Ecosystem. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11623. Springer, Cham. https://doi.org/10.1007/978-3-030-24308-1_24

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  • DOI: https://doi.org/10.1007/978-3-030-24308-1_24

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-24308-1

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