Context representation and fusion: advancements and opportunities

Sensors (Basel). 2014 May 30;14(6):9628-68. doi: 10.3390/s140609628.

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 research. A detailed review on both the processes is provided in this research with their applications. Future research directions (challenges) are also highlighted which needs proper attention for the purpose of achieving the goal of realizing context-aware systems.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Automobile Driving
  • Biometric Identification
  • Computing Methodologies*
  • Delivery of Health Care, Integrated*
  • Environmental Monitoring*
  • Humans
  • Internet
  • Models, Theoretical*
  • Semantics
  • Signal Processing, Computer-Assisted*