It often takes days to analyze information, from photos of individuals to human intelligence, gathered by soldiers in the field. These delays lead to missed opportunities, such as the failure to identify and capture persons of interest. While sophisticated network analytics and strategies are available, they typically rely on access to big data that is available only in garrison, employ heavyweight analytics algorithms, and are not adaptable to situational demands and resources of soldiers on a mission.
This exploratory project aims to improve the analysis of information gathered by soldiers in the field, by guiding the type and fidelity of the analysis. To achieve this, the project is investigating lightweight, ready-to-field network-analysis algorithms and use of sensed contextual information. This work will support decision making in the field by enabling users to trade timeliness and fidelity of responses to get sufficient information at the right time. Dismounted soldiers will be able to access these capabilities even when they are disconnected from the enterprise network.
Lewis, Grace; Boleng, Jeff; Cahill, Gene; Morris, Edwin; Novakouski, Marc; Root, James; & Simanta, Soumya. "Architecture Patterns for Mobile Systems in Resource-Constrained Environments." Presented at the Software Engineering Institute Architecture Technology User Network (SATURN) Conference, Minneapolis, MN, May 2013.
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