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phat 21(28): e5

Research Article

ASSISTO eCARE 4.0 -- An IoT- and AI-based architecture for assisted active aging

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  • @ARTICLE{10.4108/eai.6-8-2021.170666,
        author={Leonardo Bertini and Dario Bruneo and Massimo Mecella and Emilia Reda},
        title={ASSISTO eCARE 4.0 -- An IoT- and AI-based architecture for assisted active aging},
        journal={EAI Endorsed Transactions on Pervasive Health and Technology},
        volume={7},
        number={28},
        publisher={EAI},
        journal_a={PHAT},
        year={2021},
        month={8},
        keywords={wellness, safety, active aging, artificial intelligence, machine learning, remote monitoring},
        doi={10.4108/eai.6-8-2021.170666}
    }
    
  • Leonardo Bertini
    Dario Bruneo
    Massimo Mecella
    Emilia Reda
    Year: 2021
    ASSISTO eCARE 4.0 -- An IoT- and AI-based architecture for assisted active aging
    PHAT
    EAI
    DOI: 10.4108/eai.6-8-2021.170666
Leonardo Bertini1, Dario Bruneo2,3, Massimo Mecella4,*, Emilia Reda5
  • 1: Assisto, Italy
  • 2: smartme.IO, Italy
  • 3: Università di Messina, Dipartimento di ingegneria, Italy
  • 4: Sapienza Università di Roma, Dipartimento di ingegneria informatica automatica e gestionale, Italy
  • 5: Giomi RSA, Italy
*Contact email: massimo.mecella@uniroma1.it

Abstract

INTRODUCTION: All over Europe, there is an increasing demand for social/welfare services and a shift towards a demand increasingly formed by a mix of well-being and safety. Artificial intelligence (AI), Internet-of-Things (IoT) and cloud computing techniologies can play a major role in such a type of services.

OBJECTIVES: The aim of this work was to investigate, design, develop and validate a prototype platform, named Assisto eCare 4.0, providing “well-being” and “safety” services/functionalities to home elderly residents.

METHODS: The platform builds upon biometric technologies and analytics functionalities exploiting AI techniques in order to limit human intervention during emergencies and automatically and immediately deciding actions to be performed by making the operators intervene also directly at the user home.

RESULTS: The prototype has been validated with a group of 22 users over a period of more than 7 months. The results derived from the final evaluation questionnaire show that the majority of participants rated the service as excellent.

CONCLUSIONS: The platform has been released according to the API-as-a-Service model, proposing itself with a pioneering model of social open innovation, which is to develop and test the IT system and then to make it available to all those who want to use it. Currently (July 2021) the system has been engineered and offered by a consortium of different industries and is operative in the Rome area.

Keywords
wellness, safety, active aging, artificial intelligence, machine learning, remote monitoring
Received
2020-05-31
Accepted
2021-07-17
Published
2021-08-06
Publisher
EAI
http://dx.doi.org/10.4108/eai.6-8-2021.170666

Copyright © 2021 Leonardo Bertini et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.

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