Abstract
Web of Things applications require advanced solutions to provide adaptation to different purposes from common context models. While such models are application-specific, the adaptation itself is based on questions (i.e. concerns) that are orthogonal to application domains. In this paper, we present a generic solution to provide reusable and multi-purpose context-based adaptation for smart environments. We rely on semantic technologies and reason about contextual information to evaluate, at runtime, the pertinence of each adaptation possibility to adaptation questions covering various concerns. We evaluate our solution against a smart agriculture scenario using the ASAWoO platform, and discuss how to design context models and rules from “classical” information sources (e.g. domain experts, device QoS, user preferences).
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Notes
- 1.
Functionalities must be exposed by avatars prior to be called by clients and executed.
- 2.
One second is the commonly admitted threshold upon which the user’s attention stops focusing on the current task.
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Acknowledgement
This work is supported by the French ANR (Agence Nationale de la Recherche) under the grant number <ANR-13-INFR-012>.
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Terdjimi, M., Médini, L., Mrissa, M., Maleshkova, M. (2017). Multi-purpose Adaptation in the Web of Things. 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_17
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DOI: https://doi.org/10.1007/978-3-319-57837-8_17
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