Multi-purpose adaptation in the web of things

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).