Summaries - Research
Back CMIS 2 FY18 Research
|Division||Graduate School of Engineering & Applied Science|
|Department||Electrical & Computer Engineering|
|Investigator(s)||Scrofani, James W.|
|Sponsor||Department of Defense Space (DoD)|
Multi-INT is an interdisciplinary field seeking to understand how various data analytic related models and methodologies can vastly improve sensemaking, situation awareness and decision making.
In an era where collection of data has outpaced the ability of technology and humans to make sense of all available information, the orthodox notion of working in, or specializing in, independent, single data domains such as electronic communications, multiple types of imagery, and social media data feeds is undergoing significant reconsideration. In fact, Multi-INT approaches employed across the business processes of all types must be examined, and integrated notions of requirements generation, tasking, collection and processing must be considered.
This work seeks to produce research outcomes that significantly increase the ability of the U.S. Navy, U.S. Department of Defense, and other U.S. government agencies to better integrate multiple data streams.
|Keywords||High Risk Classification AIS Automated Detection Automated Sensemaking Brownian Bridge Motion Models Informatics and Data Fusion Logic Learning Machine Learning Approaches Maritime Domain Awareness Sensor Development Target Forecasting multi-int|
|Publications||Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal|
|Data||Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal|