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Predictive Situation Awareness (PSAW) is the ability to estimate and predict aspects of a temporally evolving situation. PSAW systems reason about complex and uncertain situations involving multiple targets observed by multiple sensors at different times. Multi-Entity Bayesian Networks (MEBN) are rich enough to represent and reason about uncertainty in complex, knowledge-rich domains, and have been...
Over the course of Dave Hall's career, he highlighted various concerns associated with the implementation of data fusion methods. Many of the issues included the role of uncertainty in data fusion, practical implementation of sensor fusion systems, and incorporating new technology into information fusion designs. These thoughts were communicated through technical books and Handbook collections of...
The probabilistic ontology language PR-OWL (Probabilistic OWL) uses Multi-Entity Bayesian Networks (MEBN), an extension of Bayesian networks with first-order logic, to add the ability to deal with uncertainty to OWL, the main language of the Semantic Web. A second version, PR-OWL 2, was proposed to allow the construction of hybrid ontologies, containing deterministic and probabilistic parts. Existing...
Accurate situational assessment is key to any decision making especially crucial in military command and control, air traffic control, and complex system decision making. Endsley describes three dependent levels of situational awareness, (1) perception, (2) understanding, and (3) projection. This research is focused on Endsley's second-level situational awareness (understanding) as it applies to service-oriented...
Network-centric operations demand an increasingly sophisticated level of interoperation and information fusion for an escalating number and throughput of sensors and human processes. The resulting complexity of the systems being developed to face this environment render lower level fusion techniques alone simply insufficient to ensure interoperability, as they fail to consider subtle, but critical,...
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