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

Bertini, Leonardo and Bruneo, Dario and Mecella, Massimo and Reda, Emilia ASSISTO eCARE 4.0 -- An IoT- and AI-based architecture for assisted active aging. EAI Endorsed Transactions on Pervasive Health and Technology, 7 (28). p. 170666. ISSN 2411-7145

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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.

Item Type: Article
Uncontrolled Keywords: wellness, safety, active aging, artificial intelligence, machine learning, remote monitoring
Subjects: Q Science > Q Science (General)
R Medicine > R Medicine (General)
Depositing User: EAI Editor IV
Date Deposited: 08 Nov 2021 07:21
Last Modified: 08 Nov 2021 07:21
URI: https://eprints.eudl.eu/id/eprint/8024

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