The A.I.zeta framework: An ontological approach for AAL systems control
Lecture Notes in Electrical Engineering, ISSN: 1876-1119, Vol: 426, Page: 223-238
2017
- 10Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Captures10
- Readers10
- 10
Book Chapter Description
The AAL Systems have been devised to monitor the life of persons in their home, in order to infer information on their state of health and to support their wellbeing. The achievement of this purpose is possible by means of various technologies and systems (such as, for instance, home environment sensors, personal sensors and clinical devices). This article describes the design and early development of a software tool, that allows to control an AAL System, completely based on an ontological approach. From this innovative point of view, an ontological formalization is used to describe a domain and to implement an automatic reason. This approach provides a dynamic model that can change its state and expand accordingly to rules that are also a part of the model. Such a description is continually updated with information provided by the AAL System database that reports the significant events recorded by the sensors. Then, exploiting the potential of an OWL-DL reasoner, decisions about the feedbacks that the System have to activate, are inferred.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85018669535&origin=inward; http://dx.doi.org/10.1007/978-3-319-54283-6_17; http://link.springer.com/10.1007/978-3-319-54283-6_17; http://link.springer.com/content/pdf/10.1007/978-3-319-54283-6_17; https://dx.doi.org/10.1007/978-3-319-54283-6_17; https://link.springer.com/chapter/10.1007/978-3-319-54283-6_17
Springer Science and Business Media LLC
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