Maritime Big Data Analytics
Navy SBIR 2019.1 - Topic N191-013
NAVAIR - Ms. Donna Attick - firstname.lastname@example.org
Opens: January 8, 2019 - Closes: February 6, 2019 (8:00 PM ET)
AREA(S): Information Systems
PROGRAM: None or N/A NAE Chief Technology Office
Evaluate the benefits of big data analytics to effectively manage the abundance
of ingested and disparate data for the purpose of enhancing the decision-making
process during maritime missions.
The success of military operations significantly depends on the level of
situational awareness. This is especially true for the P-8A Poseidon conducting
long-range anti-submarine warfare; anti-surface warfare; and intelligence,
surveillance, and reconnaissance (ISR) maritime missions. An expanding array of
sensors and disparate information sources has exponentially increased the sheer
volume and variety of data flooding operators and potentially causing operator
fatigue from data overload. The P-8A will process and analyze terabytes of data
per mission, a significant increase from the gigabytes of data for its
predecessor, the P-3. At risk is the effectiveness and efficiency of on-board
operators to manage, interpret, and take action on timely sensitive data to
neutralize potential threats.
I: Develop, design, and demonstrate a strategy, taking into consideration the
feasibility, suitability and acceptability, to leverage big data analytics for
P-8A maritime missions. Identify potential roadblocks likely to be encountered
and formulate approaches to overcome them. Recommend an architecture, such as
open source, and implementation plan and illustrate the benefits of big data
analytics through operational use cases. The Phase I effort will include
prototype plans to be developed under Phase II.
II: Develop a working prototype of the selected concept to include high level
requirements, design, initial testing, and demonstration. Demonstrate the
prototype in a lab or live environment.
III DUAL USE APPLICATIONS: Conduct integration and testing of the prototype for
the P-8A system, to include land-based mobile operational centers (MOCs), where
data analysis occurs. This capability would have multiple applications for the
private sector where large amounts of data need analysis for efficiency of
specific systems, to include banking, inventory, and commerce.
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and Widom, J. “Challenges and Opportunities with Big Data: A white paper
prepared for the Computing Community Consortium committee of the Computing Research
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Porche III, I., Wilson, B., Jonhson, E.-E., Tierney, S., and Saltzman, E.
“data_flood: Helping the Navy Address the Rising Tide of Sensor Information.”
RAND Corporation: Santa Monica. https://www.rand.org/content/dam/rand/pubs/research_reports/RR300/RR315/RAND_RR315.pdf
Ramos, J., and Ranjan, R. “Cognitive Data Governance Powered by Machine
Learning to Find and Use Governed Data.” IBM Corporation: Somers, NY, 2018. https://kapost-files-prod.s3.amazonaws.com/uploads/asset/file/5b0440c579aff3001d0000be/CDG_Jo_Rakesh.pdf
Big Data; Analytics; Decision Making; Automation; Disparate Sources;