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UBITECH presents a scientific paper on Semantic Web technologies for elderly home mobilization at SWH 2018 in Monterey, CA

A scientific paper entitled “An Ontology-Driven Elderly People Home Mobilization Approach” has been edited by UBITECH and is presented at the First International Workshop on Semantic Web Technologies for Health Data Management (SWH 2018) Workshop that is co-located with the 17th International Semantic Web Conference (ISWC 2018), hosted between October 8-12, 2018 in Monterey, California, USA. In this paper, Sophia Karagiorgou, Dimitris Ntalaperas, Georgios Vafeiadis, Dimitris Alexandrou and their co-authors propose a semantic interoperability agent which exploits mobility tracking and spatiotemporal characteristics to extract human profiling and give incentives for mobilization at home. The agent takes advantage of an extended ontology which facilitates the collation of evidence for the effects of exergaming on the movement control of older adults. In order to provide personalized monitoring services, a number of rules are individually defined to generate incentives. To evaluate the proposed semantic interoperability agent, human mobility data are collected and analyzed based on daily activities, their duration and mobility patterns. We show that the proposed agent is robust enough for activity classification, and that the recommendations for mobilization are accurate. We further demonstrate the agent’s potential in useful knowledge inference regarding personalized elderly people home care.

As the goal of this work is to contribute to personalized home care of elderly people by developing an ontology-driven semantic interoperability agent that facilitates diverse human mobility activities to be captured and monitored for motivating further incentives and recommendations, we, more particularly (a) introduce a semantic interoperability agent that builds a knowledge base and autonomously learns from the individual playing habits, what kind of games are preferred by the user, as well as her playing skills from the game performance, and uses this information to provide personalized and inspiring incentives for future mobilization; (b) extend a data model described by a standards-based schema ontology which is familiar to domain experts and expose data in a standardized format by supporting interoperability with existing systems and other services; and (c) evaluate the semantic interoperability agent using real-world datasets demonstrating its effectiveness and efficiency. The outcome is a personalized mobility model that is used to provide recommendations and incentives to the end-user.