KEYWORDS: Artificial intelligence, Data fusion, Data modeling, Chemical elements, Information security, Signals intelligence, Visualization, Image processing, Sensors, Telecommunications
This document presents a case for applying multiple sources of intelligence and various
fusion methodologies to the problem of providing maritime domain awareness for in both
the open ocean and for the areas outside of ports and harbors.
KEYWORDS: Artificial intelligence, Data fusion, Signals intelligence, Data modeling, Chemical elements, Image processing, Data centers, Internet, System identification, Sensors
The international community's focus on deterring terrorism has identified many vulnerabilities to a country's borders. These vulnerabilities include not only airports and rail lines but also the ports, harbors and miles of coastline which many countries must protect. In seeking to address this challenge, many technologies, processes and procedures have been identified that utilize single point or single source INT's (i.e., sources of intelligence - signals: SIGINT, imagery: IMINT, and open-source: INTERNET). These single source data sets include the information gleaned from shipping lines, port arrival and departure information and information from shipboard based electronic systems like the Automatic Identification System (AIS). Typically these are evaluated and incorporated into products or decisions in a singular manner and not with any reference or relationship to each other. In this work, an identification and analysis of these data sets will be performed in order to determine:
•Any commonality between these data sets,
•The ability to fuse information between these data sets,
•The ability to determine relationships between these data sets, and
•The ability to present any fused information or relationships in a timely manner
In summary, the work served as a means for determining the data sets that were of the highest value and for determining the fusion method for producing a product of value. More work can be done to define the data sets that have the most commonality and thus will help to produce a fused product in the most timely and efficient manner.
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