Situational Awareness: Techniques, Challenges, and Prospects

被引:60
作者
Munir, Arslan [1 ]
Aved, Alexander [2 ]
Blasch, Erik [3 ]
机构
[1] Kansas State Univ, Dept Comp Sci, Manhattan, KS 66506 USA
[2] US Res Lab AFRL, Informat Directorate, Rome, NY 13441 USA
[3] AFRL Off Sci Res AFOSR, 875 North Randolph St, Arlington, VA 22203 USA
关键词
situational awareness; dynamic data-driven systems; artificial intelligence; synthetic vision systems; fog computing; gray zone warfare; ARTIFICIAL-INTELLIGENCE;
D O I
10.3390/ai3010005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Situational awareness (SA) is defined as the perception of entities in the environment, comprehension of their meaning, and projection of their status in near future. From an Air Force perspective, SA refers to the capability to comprehend and project the current and future disposition of red and blue aircraft and surface threats within an airspace. In this article, we propose a model for SA and dynamic decision-making that incorporates artificial intelligence and dynamic data-driven application systems to adapt measurements and resources in accordance with changing situations. We discuss measurement of SA and the challenges associated with quantification of SA. We then elaborate a plethora of techniques and technologies that help improve SA ranging from different modes of intelligence gathering to artificial intelligence to automated vision systems. We then present different application domains of SA including battlefield, gray zone warfare, military- and air-base, homeland security and defense, and critical infrastructure. Finally, we conclude the article with insights into the future of SA.
引用
收藏
页码:55 / 77
页数:23
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