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Causal Models for Safety Assurance Technologies

Award Information

Agency:
National Aeronautics and Space Administration
Branch:
N/A
Award ID:
Program Year/Program:
2012 / SBIR
Agency Tracking Number:
115057
Solicitation Year:
2011
Solicitation Topic Code:
A1.17
Solicitation Number:
Small Business Information
Aptima, Inc.
12 Gill Street Suite 1400 Woburn, MA 01801-
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2012
Title: Causal Models for Safety Assurance Technologies
Agency: NASA
Contract: NNX12CD01P
Award Amount: $124,937.00
 

Abstract:

Fulfillment of NASA's System-Wide Safety and Assurance Technology (SSAT) project at NASA requires leveraging vast amounts of data into actionable knowledge. Models of accident causation describe a causation chain. The chain would be better understood by examining the large amounts of "everyday" flight data, not just data proximal to high-profile incidents. This proposal is focused on the detection and prediction of more common flight errors or conditions which are necessary for aviation incidents. However, data sets containing safety information are (1) large, (2) distributed, and (3) heterogeneous, making analysis difficult. In order to address these challenges, we propose Causal Models for Safety and Assurance Technologies (CM-SAT). CM-SAT will mine large, distributed, heterogeneous data systems for causal relationships about flight safety. The system will identify causal schema within the data that characterize conditions related to the aircraft and environment that are predictive of failures. CM-SAT will detect causal relationships at varying levels of granularity (e.g. relationships which are unique to a particular flight, to a particular aircraft model, or to a particular fleet). It will leverage state-of-the-art distributed meta-reasoning, which will direct the causal schema learning algorithms to detect and validate causal relationships in different parts of the distributed data sets.

Principal Investigator:

Jennifer Roberts
Principal Investigator
7814962304
jroberts@aptima.com

Business Contact:

Gino Cascieri
Business Official
7814962462
gcascieri@aptima.com
Small Business Information at Submission:

Aptima, Inc.
12 Gill Street Suite 1400 Woburn, MA -

EIN/Tax ID: 043281859
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No