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Topological Data Analysis and Wide Area Detection of Chemical and Biological Contamination

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911SR-10-P-0029
Agency Tracking Number: A10A-020-0278
Amount: $99,985.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: A10A-T020
Solicitation Number: 2010.A
Solicitation Year: 2010
Award Year: 2010
Award Start Date (Proposal Award Date): 2010-09-27
Award End Date (Contract End Date): 2011-03-29
Small Business Information
1142A Old York Road
Ringoes, NJ 08551
United States
DUNS: 132562765
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Daniel Kling
 (908) 237-1955
Business Contact
 Robert Torbin
Title: Director of Business Development
Phone: (617) 347-9065
Research Institution
 University of Minnesota
 Ren Guo
206 Church Street SE
Minneapolis, MN 55455
United States

 (612) 625-1119
 Nonprofit College or University

Topological data analysis is a new mathematical method used to study these massive data sets that arise in a variety of situations including military operations and national security. The use of passive infrared sensors for a wide area detection system involving chemical and biological contaminants produces massive amounts of hyperspectral image data. Recent research in this area include fast algorithms for computing homology dimension, the extension of homology from sets to distributions and functions, and a smart convolution filter that interprets local topological features that span between user defined geometric boundaries. Together these innovations give a new morphology grammar implemented through the geometry of the filter, its density distribution values, and iteration with other statistical procedures that extracts and manipulates the desired information in the most effective and efficient manner possible. If successfully demonstrated, the use of homology could change the very nature of data analyses for a multitude of national security and military situations where the current statistical methods are not capable of detecting qualitative structures.

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

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