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Conference Papers Year : 2017

The ContextAct@A4H real-life dataset of daily-living activities Activity recognition using model checking

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Abstract

Research on context management and activity recognition in smart environments is essential in the development of innovative well adapted services. This paper presents two main contributions. First, we present ContextAct@A4H, a new real-life dataset of daily living activities with rich context data 4. It is a high quality dataset collected in a smart apartment with a dense but non intrusive sensor infrastructure. Second, we present the experience of using temporal logic and model checking for activity recognition. Temporal logic allows specifying activities as complex events of object usage which can be described at different gran-ularity. It also expresses temporal ordering between events thus palliating a limitation of ontology based activity recognition. The results on using the CADP toolbox for activity recognition in the real life collected data are very good.
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Dates and versions

hal-01551418 , version 1 (30-06-2017)

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Paula Lago, Frederic Lang, Claudia Roncancio, Claudia Jiménez-Guarín, Radu Mateescu, et al.. The ContextAct@A4H real-life dataset of daily-living activities Activity recognition using model checking. 10th International and Interdisciplinary Conference - CONTEXT 2017, Jun 2017, Paris, France. pp.175-188, ⟨10.1007/978-3-319-57837-8_14⟩. ⟨hal-01551418⟩
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