| This research presents a model of situation awareness based on a dynamic decision making machine. Situation awareness is presented as a pressing concern in systems operation in a wide variety of environments. This study utilizes the relationship between situation awareness, individuals and environmental factors to come up with final security decisions. In general, these factors are useful in acquiring and interpreting information from the environment to form a behavior conclusion. The model is used to enhance an operator's situation awareness sense. Because the process of decision making is becoming increasingly complex, the research community has devoted great attention to developing strategic understanding and to its implementation.;Often uncertain data may offer enough to make a decision, like a fighting soldier would make a decision to either fire, hold fire or totally ignore an event based on a good mix of the rules of battle engagement and the data collected, filtered and integrated.;In this research, we have selected several relevant sensors (Laser, Sonar and RF sensors) to cooperate in monitoring the security status of multiple dynamic agent surveillance area. This proposed system exhibits promising performance improvements as a result of utilizing sensor similarity and complementarity especially when heterogeneous sensors are employed.;This security system sensor fusion is aided by the Kalman Filter and Extended Kalman Filter in order to estimate an agent's next status in a noisy environment. In addition, degrees of perceived suspicious behavior are assigned from well trained and designed fuzzy (type-2 fuzzy logic) and hyper-fuzzy decision making sub-systems.;There are many sources of data available in a given environment, so whether the mission is a war in a battle field or a defense of the homeland, decisions must be made based on the information available in that environment. Information comes from multiple sources, which are sometimes in distinct formats, so users need a way to integrate it for a comprehensive understanding of events.;The ideas of fuzzy sets and the membership functions of type-1 and type-2 are illustrated along with the idea of the foot print of uncertainty (FOU). |
