Multi-criteria Fusion of Heterogeneous Information for Improving Situation Awareness on Emergency Management Systems

Information Fusion is the synergic integration of data from different sources for the support to decision-making. The emergency management systems predominance of such application has driven the development to new and better sensors, new methods, for data processing and architectures that promote access, composition, refinement and information handling, with the active participation of specialists as data providers and specialists of the systems. In this scenario of data fusion, uncertainty of diverse natures can be aggregated to both data and information at different levels of the process, creating distorted information to the specialist. As a result the situation awareness and cognitive process can be affected leading to poor quality support to decision-making as a generalization of information quality, uncertainty need to be reduced to improve awareness about the situation of interest. The objective of our work is the mitigation of uncertainty propagated by other quality attributes such as information completeness, so specialists can be able to convey an improved understanding. For such, a new fusion framework fed by multi-criteria parameterization, including information quality measures and its semantics, is depicted as an engine to build more accurate information from diverse sensed possibilities. A case study with a situation assessment application is in course to validate the effectiveness of the generated solution. Preliminary and promising results are discussed as a more valuable tool to support decision-making.