Continuous preservation of situational awareness through incremental/stochastic graphical methods
Geoff A. Gross, Rakesh Nagi, Kedar Sambhoos · International Conference on Information Fusion · 2011
Intelligence analysis in a counter-insurgency (COIN) environment requires the consideration of many sources of information which are continuously reporting on the current state of the world. Methods to incorporate the uncertainties present in these sources of information have been identified and implemented within a graph matching algorithm, which provides a situation assessment. Thus far, the methods developed have been concerned only with a static view of the world. While these methods are able to obtain situational awareness for a discrete point in time, it is clearly desirable to have continuous, or real time situational awareness. This paper describes the extensions which will enable the continuous preservation of situational awareness through the use of incremental methods and intelligent increment batching. Streaming sensor reports are implemented via a service-oriented architecture.