Context Awareness Framework Based on Contextual Graph
Tam Van Nguyen, Wontaek Lim, Huy Nguyen, and Deokjai Choi

TL;DR
This paper introduces a context-awareness framework utilizing contextual graphs to model the relationships among different contexts, aiming to improve automatic adaptation in pervasive computing systems.
Contribution
It proposes a novel use of contextual graphs to represent mutual relationships among contexts, enhancing context reasoning for better system adaptation.
Findings
Improves automatic context adaptation in pervasive systems
Facilitates context reasoning for developers
Enhances user satisfaction by reducing unexpected behaviors
Abstract
Nowadays computing becomes increasingly mobile and pervasive. One of the important steps in pervasive computing is context-awareness. Context-aware pervasive systems rely on information about the context and user preferences to adapt their behavior. However, context-aware applications do not always behave as user's desire, and can cause users to feel dissatisfied with unexpected actions. To solve these problems, context-aware systems must provide mechanisms to adapt automatically when the context changes significantly. The interesting characteristic of context is its own behaviors which depend on various aspects of the surrounding contexts. This paper uses contextual graphs to solve the problem "the mutual relationships among the contexts". We describe the most relevant work in this area, as well as ongoing research on developing context-aware system for ubiquitous computing based on…
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Taxonomy
TopicsContext-Aware Activity Recognition Systems · IoT and Edge/Fog Computing · Opportunistic and Delay-Tolerant Networks
