NASA SBIR 2015 Solicitation

FORM B - PROPOSAL SUMMARY


PROPOSAL NUMBER: 15-1 A3.03-8942
SUBTOPIC TITLE: Future Aviation Systems Safety
PROPOSAL TITLE: Big Data Driven Architecture for Real Time Systemwide Safety Assurance

SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
ATAC
2770 De La Cruz Boulevard
Santa Clara, CA 95050 - 2624
(408) 736-2822

PRINCIPAL INVESTIGATOR/PROJECT MANAGER (Name, E-mail, Mail Address, City/State/Zip, Phone)
John Schade
jes@atac.com
2770 De La Cruz Blvd.
Santa Clara, CA 95050 - 2624
(408) 736-2822

CORPORATE/BUSINESS OFFICIAL (Name, E-mail, Mail Address, City/State/Zip, Phone)
Charles Winkleman
cew@atac.com
2770 De La Cruz Blvd.
Santa Clara, CA 95050 - 2624
(408) 736-2822

Estimated Technology Readiness Level (TRL) at beginning and end of contract:
Begin: 2
End: 5

Technology Available (TAV) Subtopics
Future Aviation Systems Safety is a Technology Available (TAV) subtopic that includes NASA Intellectual Property (IP). Do you plan to use the NASA IP under the award?
No

TECHNICAL ABSTRACT (Limit 2000 characters, approximately 200 words)
NASA has the aim of researching aviation Real-time System-wide Safety Assurance (RSSA) with a focus on the development of prognostic decision support tools as one of its new aeronautics research pillars. The vision of RSSA is to accelerate the discovery of previously unknown safety threats in real time and enable rapid mitigation of safety risks through analysis of massive amounts of aviation data. Our innovation supports this vision by designing a hybrid architecture combining traditional database technology and real-time streaming analytics in a Big Data environment. The innovation includes three major components: a Batch Processing framework, Traditional Databases and Streaming Analytics. It addresses at least three major needs within the aviation safety community. First, the innovation supports the creation of future data-driven safety prognostic decision support tools that must pull data from heterogeneous data sources and seamlessly combine them to be effective for NAS stakeholders. Second, our innovation opens up the possibility to provide real-time NAS performance analytics desired by key aviation stakeholders. Third, our proposed architecture provides a mechanism for safety risk accuracy evaluations. To accomplish this innovation, we have three technical objectives and related work plan efforts. The first objective is the determination of the system and functional requirements. We identify the system and functional requirements from aviation safety stakeholders for a set of use cases by investigating how they would use the system and what data processing functions they need to support their decisions. The second objective is to create a Big Data technology-driven architecture. Here we explore and identify the best technologies for the components in the system including Big Data processing and architectural techniques adapted for aviation data applications. Finally, our third objective is the development and demonstration of a proof-of-concept.

POTENTIAL NASA COMMERCIAL APPLICATIONS (Limit 1500 characters, approximately 150 words)
Provide a Big Data technology-driven architecture with safety prognostics capability in supporting RSSA that can address safety risk/hazard identification techniques on large quantities of historical NAS data and streaming live aviation data.
Assist ATM researchers directly by enhancing the capabilities of the ATM Data Warehouse with these techniques.
Allow ongoing data mining efforts to utilize Big Data technology to enhance the performance of these safety algorithms, dramatically allowing for faster discovery of more safety or performance anomalies and eventually predicting safety risk and precursors in near real time.
Enhance the capabilities of SMART-NAS for researchers to quickly examine the system-wide safety implications of new concepts and technologies, and address the design and operational mitigations of safety risks.

POTENTIAL NON-NASA COMMERCIAL APPLICATIONS (Limit 1500 characters, approximately 150 words)
Enable key FAA operational facility safety personnel to have performance dashboards driven by Big Data-based, near real-time analytics to alert them when the NAS or regional areas are experiencing or could experience safety risk.
Allow airlines to turn vast amounts of FOQA data and other information gathered from operations into "actionable" information by improving turnaround time for analysis and expanding the range of questions that can be asked of the data sets that they do maintain.
Enable airline safety personnel to monitor and predict their fleet and pilot safety performance to better predict where accidents might happen using the large amount of FOQA and/or other airlines' data that the airlines have been collecting.
Enable international Air Navigation Service Provider safety personnel to monitor and predict system threats.

TECHNOLOGY TAXONOMY MAPPING (NASA's technology taxonomy has been developed by the SBIR-STTR program to disseminate awareness of proposed and awarded R/R&D in the agency. It is a listing of over 100 technologies, sorted into broad categories, of interest to NASA.)
Air Transportation & Safety
Analytical Methods
Computer System Architectures
Data Acquisition (see also Sensors)
Data Fusion
Data Input/Output Devices (Displays, Storage)
Data Modeling (see also Testing & Evaluation)
Data Processing
Knowledge Management
Software Tools (Analysis, Design)

Form Generated on 04-23-15 15:37