A Distributed and Standard based Data Warehouse and Mining System for Large-Scale Sensor Data

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-11-M-0077
Agency Tracking Number: O102-L05-4180
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2011
Solicitation Year: 2010
Solicitation Topic Code: OSD10-L05
Solicitation Number: 2010.2
Small Business Information
15400 Calhoun Drive, Suite 400, Rockville, MD, -
DUNS: 161911532
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 Kaizhi Tang
 Senior Research Scientist
 (301) 294-5214
Business Contact
 Mark James
Title: Director, Contracts&Proposals
Phone: (301) 294-5221
Email: mjames@i-a-i.com
Research Institution
Intelligent Automation, Inc. (IAI), along with our collaborators propose to develop a Distributed and Standard based Data Warehouse and Mining System for Large-Scale Sensor Data (DSDWM). DSDWM is a synergy of SensorML based database system, streamed and high-dimensional data cubing approaches. Our stream cubing architecture is designed to handle streamed sensor data with quick response and partial computation of data cubes by popular-path cubing. The DSDWM innovations are: (1) SensorML schema database to develop a solid and extendable data storage system for large amount of complex sensor data (2) unique innovative high-dimensional data cubing technology, (3) internal data mining tool that adopts a generic framework of data mining, to provide advanced data exploitation and analysis capability beyond cubing technology, and (4) AJAX on mobile devices to enable asynchronous communication so that the bandwidth is saved. DSDWM offers the key advantage that multi-source sensor input data can be transferred to minimal cubing thus saving computation and storage expense significantly for high-dimensional cubes and prediction cubes provide an automatic and intelligent way to build cubes with optimized accuracy for a large range of prediction models.

* Information listed above is at the time of submission. *

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