KEYWORDS: Sensors, Information fusion, Data fusion, Intelligence systems, Data modeling, Web 2.0 technologies, Sensor networks, Defense and security, Analytics, Data communications
With the plethora of information, there are many aspects to contested environments such as the protection of information, network privacy, and restricted observational and entry access. In this paper, we review and contrast the perspectives of challenges and opportunities for future developments in contested environments. The ability to operate in a contested environment would aid societal operations for highly congested areas with limited bandwidth such as transportation, the lack of communication and observations after a natural disaster, or planning for situations in which freedom of movement is restricted. Different perspectives were presented, but common themes included (1) Domain: targets and sensors, (2) network: communications, control, and social networks, and (3) user: human interaction and analytics. The paper serves as a summary and organization of the panel discussion as towards future concerns for research needs in contested environments.
Multi-Intelligence (multi-INT) data includes video, text, and signals that require analysis by operators. Analysis methods
include information fusion approaches such as filtering, correlation, and association. In this paper, we discuss the Video
Event Segmentation with Text (VEST) method, which provides event boundaries of an activity to compile related message
and video clips for future interest. VEST infers meaningful activities by clustering multiple streams of time-sequenced
multi-INT intelligence data and derived fusion products. We discuss exemplar results that segment raw full-motion video
(FMV) data by using extracted commentary message timestamps, FMV metadata, and user-defined queries.
This paper describes an approach to effects-based planning in which a strategic-theater-level mission is refined into operational-level and ultimately tactical-level tasks and desired effects, informed by models of the expected enemy response at each level of abstraction. We describe a strategy development system that implements this approach and supports human-in-the-loop development of an effects-based plan. This system consists of plan authoring tools tightly integrated with a suite of center of gravity (COG) and target system analysis tools. A human planner employs the plan authoring tools to develop a hierarchy of tasks and desired effects. Upon invocation, the target system analysis tools use reduced-order models of enemy centers of gravity to select appropriate target set options for the achievement of desired effects, together with associated indicators for each option. The COG analysis tools also provide explicit models of the causal mechanisms linking tasks and desired effects to one another, and suggest appropriate observable indicators to guide ISR planning, execution monitoring, and campaign assessment. We are currently implementing the system described here as part of the AFRL-sponsored Effects Based Operations program.
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