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Title
Abstract
Introduction
Sensors and Raw Data Acquisition
Tweet Analysis Trajectory Analysis
Type Reference Method
Context Fusion Based on Probabilistic Methods
Critical Review
Discussion
Context Analysis
Sensors Data Fusion
Data Redundancy
Conclusions
References
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Analytical Chemistry

Context Representation and Fusion: Advancements and Opportunities

Profile image of Mohammad AazamMohammad Aazam

2014, Sensors

https://doi.org/10.3390/S140609628
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41 pages

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Abstract

The acceptance and usability of context-aware systems have given them the edge of wide use in various domains and has also attracted the attention of researchers in the area of context-aware computing. Making user context information available to such systems is the center of attention. However, there is very little emphasis given to the process of context representation and context fusion which are integral parts of context-aware systems. Context representation and fusion facilitate in recognizing the dependency/relationship of one data source on another to extract a better understanding of user context. The problem is more critical when data is emerging from heterogeneous sources of diverse nature like sensors, user profiles, and social interactions and also at different timestamps. Both the processes of context representation and fusion are followed in one way or another; however, they are not discussed explicitly for the realization of context-aware systems. In other words most of the context-aware systems underestimate the importance context representation and fusion. This research has explicitly focused on the importance of both the processes of context representation and fusion and has streamlined their existence in the overall architecture of context-aware systems' design and development. Various applications of context representation and fusion in context-aware systems are also highlighted in this OPEN ACCESS Sensors 2014, 14 9629

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