Abstract
The quality of context information is still one of the most overlooked factors by developers and end-users, and this makes context-aware applications less reliable. While there is recent work in this area that focuses on identifying and modeling relevant quality parameters for context information, software developers still have not yet adopted these solutions at large because they do not offer the right set of abstractions that they are familiar with. This paper presents model and language constructs, as well as software engineering tools to address these quality of context concerns. We demonstrate our overarching solution on a non-trivial Ambient Assisted Living scenario involving assistance services for the elderly supported by indoor localization technologies.
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Hoyos, J.R., Preuveneers, D., García-Molina, J.J. (2017). Quality Parameters as Modeling Language Abstractions for Context-Aware Applications: An AAL Case Study. In: Brézillon, P., Turner, R., Penco, C. (eds) Modeling and Using Context. CONTEXT 2017. Lecture Notes in Computer Science(), vol 10257. Springer, Cham. https://doi.org/10.1007/978-3-319-57837-8_46
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DOI: https://doi.org/10.1007/978-3-319-57837-8_46
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