http://www.cnr.it/ontology/cnr/individuo/prodotto/ID302128
Using Temporal Logic and Model Checking in Automated Recognition of Human Activities for Ambient-Assisted Living (Articolo in rivista)
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- Label
- Using Temporal Logic and Model Checking in Automated Recognition of Human Activities for Ambient-Assisted Living (Articolo in rivista) (literal)
- Anno
- 2013-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1109/TSMC.2013.2283661 (literal)
- Alternative label
Magherini T., Fantechi A., Nugent C., Vicario E. (2013)
Using Temporal Logic and Model Checking in Automated Recognition of Human Activities for Ambient-Assisted Living
in IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Reviews
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Magherini T., Fantechi A., Nugent C., Vicario E. (literal)
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- http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6670821 (literal)
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- Department of Information Engineering, University of Florence, Italy; Department of Information Engineering, University of Florence, Italy - CNR-ISTI, Pisa, Italy; University of Ulster, Ireland; Department of Information Engineering, University of Florence, Italy (literal)
- Titolo
- Using Temporal Logic and Model Checking in Automated Recognition of Human Activities for Ambient-Assisted Living (literal)
- Abstract
- Automated monitoring and the recognition of activities of daily living (ADLs) is a key challenge in ambient-assisted living (AAL) for the assistance of the elderly. Within this context, a formal approach may provide a means to fill the gap between the low-level observations acquired by sensing devices and the high-level concepts that are required for the recognition of human activities. We describe a system named ARA (Automated Recognizer of ADLs) that exploits propositional temporal logic and model checking to support automated real-time recognition of ADLs within a smart environment. The logic is shown to be expressive enough for the specification of realistic patterns of ADLs in terms of basic actions detected by a sensorized environment. The online model checking engine is shown to be capable of processing a stream of detected actions in real time. The effectiveness and viability of the approach are evaluated within the context of a smart kitchen, where different types of ADLs are repeatedly performed. (literal)
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