A Model to Promote Interaction between Humans and Data Fusion Intelligence to Enhance Situational Awareness

Abstract

The operator of a Command & Control (C2) system has a crucial role on the improvement of information that is processed through data fusion engines to provide Situational Awareness (SAW). Through direct access to data transformations, operators can improve information quality, by reducing uncertainty, according to their skills and expertise. Uncertainty, in this work, is considered an adverse condition, which can make the real information less accessible. Although relevant solutions have been reported in the literature on innovative user interfaces and approaches for quality-aware knowledge representation, these are concerned mostly on transforming the way information is graphically represented and on quantitatively mapping the quality-aware knowledge acquired from systems, respectively. There are few studies that deal more specifically with accessibility for decision-makers in safety-critical situations, such as C2, considering the aspect of data uncertainty. This paper presents a model to help researchers to build uncertainty-aware interfaces for C2 systems, produced by both data fusion and human reasoning over the information. Combined to environmental and personal factors, a tailored and enriched knowledge can be built, interchangeable with systems intelligence. A case study on the monitoring of a conflict among rival soccer fans is being implemented for the validation of the proposed solution.