Gyrard, Amelle, Sengès, Eloïse and Tabeau, Kasia (2023) Knowledge Engineering Framework for IoT Robotics Applied to Smart Healthcare and Emotional Well-Being. International Journal of Social Robotics, vol. 15 (n° 3). pp. 445-472.

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Identification Number : 10.1007/s12369-021-00821-6

Abstract

Social companion robots are getting more attention to assist elderly people to stay independent at home and to decrease their social isolation. When developing solutions, one remaining challenge is to design the right applications that are usable by elderly people. For this purpose, co-creation methodologies involving multiple stakeholders and a multidisciplinary researcher team (e.g., elderly people, medical professionals, and computer scientists such as roboticists or IoT engineers) are designed within the ACCRA (Agile Co-Creation of Robots for Ageing) project. This paper will address this research question: How can Internet of Robotic Things (IoRT) technology and co-creation methodologies help to design emotional-based robotic applications? This is supported by the ACCRA project that develops advanced social robots to support active and healthy ageing, co-created by various stakeholders such as ageing people and physicians. We demonstra this with three robots, Buddy, ASTRO, and RoboHon, used for daily life, mobility, and conversation. The three robots understand and convey emotions in real-time using the Internet of Things and Artificial Intelligence technologies (e.g., knowledge-based reasoning).

Item Type: Article
Language: English
Date: 2023
Refereed: Yes
Uncontrolled Keywords: Co-creation, Robotics, Smart health, Emotional care, Ageing, Elderly, Internet of robotic things, Cloud robotic, Artificial intelligence, Ontology, Semantic reasoning, Semantic web technologies, Reusable knowledge engineering, Semantic web of things (SWoT), Knowledge directory service, Body of knowledge
Subjects: C- GESTION
Divisions: TSM Research (Toulouse)
Site: UT1
Date Deposited: 05 Apr 2023 08:04
Last Modified: 07 Apr 2023 13:45
OAI Identifier: oai:tsm.fr:2835
URI: https://publications.ut-capitole.fr/id/eprint/45173
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