Unified modeling of quality of context and quality of situation for context-aware applications in the internet of things

Sophie Chabridon (1, 2, 3, 4) , Amel Bouzeghoub (1, 2, 3, 4) , Anis Ahmed Nacer (2, 3, 4) , Pierrick Marie (5) , Thierry Desprats (5, 6)

1 ACMES-SAMOVAR - Architecture, Cloud continuum, formal Models, artificial intElligence and Services in distributed computing
2 TSP - INF - Département Informatique
3 SAMOVAR - Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux
4 CNRS - Centre National de la Recherche Scientifique
5 IRIT-SIERA - Service IntEgration and netwoRk Administration
6 UT3 - Université Toulouse III - Paul Sabatier

This paper discusses the requirements of situation identification in the Internet of Things and the necessity to consider the quality of the input context data during the inference process for deriving a situation and evaluating its resulting quality. We propose to extend previous works by integrating the QoCIM meta-model within the muSIC framework dedicated to situation identification. Situation identification is derived using an ontological approach and Quality criteria are aggregated using the fuzzy Choquet operator for computing the quality of a situation. This paper shows that QoCIM allows to model quality of context (QoC) as well as quality of situation in a unified approach

Mots clés: Context-aware computing; Quality of situation; Internet of Things; Quality of context; Context

Domaines: Génie logiciel [cs.SE]; Informatique ubiquitaire

Sophie Chabridon, Amel Bouzeghoub, Anis Ahmed Nacer, Pierrick Marie, Thierry Desprats. Unified modeling of quality of context and quality of situation for context-aware applications in the internet of things. CONTEXT 2017 : 10th International and Interdisciplinary Conference on Modeling and Using Context, Jun 2017, Paris, France. pp.370 - 374, ⟨10.1007/978-3-319-57837-8_30⟩. ⟨hal-01614541⟩