Using Semantics to Improve Information Fusion and Increase Situational Awareness

Abstract

Situational Awareness (SAW) is the ability of a human to perceive, understand and project the states of assets in a real-world environment. In the emergency management domain, SAW is developed by means of a range of information collected from several sources, typically in real time. With this amount of information to be observed by the human operator, the development of SAW is a very complex and dynamic task. To assist this process of developing SAW, several technological and informational approaches have been developed to support decision-making systems, bringing together situational assessment routines (e.g., acquisition, processing and presentation) for the human operator to build SAW based on the information at hand, which can be very quality-limited in many aspects, depending on their source. Since such systems employ concepts and techniques of data and information fusion to perform information integration, issues regarding synergistic information association emerge. In order to enhance and improve this process, it is proposed in this paper a new fusion approach using the concepts of data quality and semantics.