MoveCare develops and field tests an innovative multi-actor platform that supports the independent living of the elder at home by monitoring, assist and promoting activities to counteract decline and social exclusion. It comprises 3 hierarchical layers: 1) A service layer provides monitoring and intervention. It endows objects of everyday use with advanced processing capabilities and integrates them in a distributed pervasive monitoring system to derive degradation indexes linked to decline. 2) A context-aware Virtual Caregiver, embodied into a service robot, is the core layer. It uses artificial intelligence and machine learning to propose to the elder a personalized mix of physical/cognitive/social activities as exergames. It evaluates the elder status, detects risky conditions, sends alerts and assists in critical tasks, in therapy and diet adherence. 3) The users’ community strongly promotes socialization acting as a bridge towards the elders’ ecosystem: other elders, clinicians, caregivers and family. Gamification glues together monitoring, lifestyle, activities and assistance inside a motivating and rewarding experience. Off-the-shelf components are assembled in a robust and reliable way to get a low-cost multi-actor IP-domotic platform that can be massively deployed at elders home. The use of software/hardware standards assures interoperability and makes MoveCare adaptable to utmost novel components. Full configurability, personalization, adaptation to elder needs applies to all components to maximize elder compliance, even when computer illiterate. On-field testing starting early in the project assures an implementation iterative approach involving all actors. MoveCare identifies functional and technical metrics to characterize and evaluate the system by means of improvement in its abilities as described by the Multi-Annual Roadmap. The metrics lead to the definition of an evaluation framework transferrable to other fields
Michael Sioutis, Zhiguo Long, Sanjiang Li Leveraging Variable Elimination for Efficiently Reasoning about Qualitative Constraints published pages: 1860001, ISSN: 0218-2130, DOI: 10.1142/S0218213018600011
International Journal on Artificial Intelligence Tools 27/04
2020-01-23
2017
M. Sioutis, A. Paparrizou, J. Condotta Collective Singleton-Based Consistency for Qualitative for Qualitative Constraint Networks published pages: 1-19, ISSN: , DOI: 10.4230/LIPIcs.TIME.2017.19
Proccedings TIME 2017 Dagstuhl, Germany
2020-01-23
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The information about "MOVECARE" are provided by the European Opendata Portal: CORDIS opendata.
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