Agile Sensor Tasking For Coist Using Natural Language Knowledge Representation And Reasoning

GROUND/AIR MULTISENSOR INTEROPERABILITY, INTEGRATION, AND NETWORKING FOR PERSISTENT ISR V(2014)

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摘要
We describe a system architecture aimed at supporting Intelligence, Surveillance, and Reconnaissance (ISR) activities in a Company Intelligence Support Team (CoIST) using natural language-based knowledge representation and reasoning, and semantic matching of mission tasks to ISR assets. We illustrate an application of the architecture using a High Value Target (HVT) surveillance scenario which demonstrates semi-automated matching and assignment of appropriate ISR assets based on information coming in from existing sensors and human patrols operating in an area of interest and encountering a potential HVT vehicle. We highlight a number of key components of the system but focus mainly on the human/ machine conversational interaction involving soldiers on the field providing input in natural language via spoken voice to a mobile device, which is then processed to machine-processable Controlled Natural Language (CNL) and confirmed with the soldier. The system also supports CoIST analysts obtaining real-time situation awareness on the unfolding events through fused CNL information via tools available at the Command and Control (C2). The system demonstrates various modes of operation including: automatic task assignment following inference of new high-importance information, as well as semi-automatic processing, providing the CoIST analyst with situation awareness information relevant to the area of operation.
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关键词
data-to-decisions, sensor-tasking, controlled natural language, ontologies, conversational interaction
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