Deep Analytics for Data in Cyber-Physical Systems

Period of Performance: 03/18/2014 - 09/18/2014

$150K

Phase 1 SBIR

Recipient Firm

Edaptive Computing, Inc.
1245 Lyons Road Array
Dayton, OH 45458
Principal Investigator

Abstract

Our proposal specifically addresses the stated requirements of the solicitation; we will develop and deploy tools, methods, and models for improving collaboration between human and cyber-physical systems. The proposed HARVEST solution builds on previous Edaptive Computing, Inc (ECI) knowledge and technology itself innovative to create a knowledge discovery system which extracts and integrates cyber-physical system, as well as presenting informative and useful visualizations to the user. The resulting capabilities will be improved data analysis and human-cyber-physical system interaction. Prior experience and new research has already shown that ECI s innovative tools suite will be clearly adaptive to knowledge discovery and integration algorithms, hypothesis generation, and visualization algorithms. The DoD has increasingly emphasized automation of tasks that have been performed historically by humans, including data analysis. However, the cyber and physical systems are highly complex, resulting in complicated data output and providing a significant obstacle to human analysts understanding. These problems must be addressed for the DoD to remain successful as technology continues to evolve rapidly. In response to these issues, Edaptive Computing Inc. presents an innovative solution that specifically addresses the OSD s requirements and provides a significant step towards an improved data analysis and visualization platform.