Accession Number:

AD1047451

Title:

DATA MAYHEM VERSUS NIMBLE INFORMATION: TRANSFORMING HECTIC IMAGERY INTELLIGENCE DATA INTO ACTIONABLE INFORMATION USING ARTIFICIAL NEURAL NETWORKS

Descriptive Note:

Technical Report

Corporate Author:

AIR COMMAND AND STAFF COLLEGE DISTANCE LEARNING AIR UNIVERSITY MAXWELL AFB United States

Personal Author(s):

Report Date:

2017-10-01

Pagination or Media Count:

39.0

Abstract:

The current Processing, Exploitation and Dissemination PED process does not satisfy the demands for intelligence to warfighters. Data production rate from Imagery Intelligence IMINT sensors far exceed the current capacity to process and analyze it, making the PED process a choke point for intelligence reaching combat forces in a timely manner. The demand for intelligence is, and will continue to be, on the rise for the foreseeable future. Artificial Neural Networks ANN, allows for faster data processing and analysis, leveraging technology in favor of the IMINT analysis process. This paper answers the question of how can ANN effectively transform IMINT data into reliable and timely intelligence for combat commanders. The purpose of this work is to open the appetite for a material solution that can be implemented. Using technical explanations with a problemsolution framework and focus, this paper articulates the solution to the research question. Conclusions express how ANN systems evolve, signaling a suitable solution for the problem of handling big data. Recommendations are to explore the implementation of ANN at the core of the PED process in order to make it more agile in processing and analyzing data. Due to the complexity of designing and deploying ANN, the scope of this research is limited to conceptual technical details. This paper is not intended to provide a technical solution for implementation

Subject Categories:

  • Military Intelligence
  • Information Science

Distribution Statement:

APPROVED FOR PUBLIC RELEASE