Adaptive Situation Awareness Using Visual Analytics

Abstract

The accurate estimation of environment is a precursor to awareness of the situation around subject(s) of interest. It is imperative that awareness leads to better, improved and safer surroundings and in many cases averts disasters. Following clues from human cognitive nature there have been a significant progress in the development of situation awareness (SAW) models and its implementation in wide ranging industrial, medical and defense applications. The information collected, when utilized in hierarchical order of priority, allows for accurate decision making up to certain degree of confidence. The challenges faced in current applications are the dissemination of information and its demonstration to make artificially intelligent decisions when it goes beyond the perception or comprehension of human mind. In this paper a design methodology is detailed related to adaptive situation awareness (SAW), and the components that are required for its development. The features of intelligent visual analytics and its importance in the development of SAW are also explained. Finally an approach is laid out for arriving at an adaptive SAW with the help of visual analytics model in a bottom up approach, starting from data generation, fusion, logical search algorithm, protocol development and using mathematical modeling for probabilistic approach to a certainty based adaptive SAW model.