Large-Asset, Intelligent, Composite-Matrix, Multifunctional Sensor Networks

Award Information
Agency:
Department of Defense
Branch
Defense Advanced Research Projects Agency
Amount:
$98,996.00
Award Year:
2004
Program:
SBIR
Phase:
Phase I
Contract:
W31P4Q-04-C-R380
Award Id:
68843
Agency Tracking Number:
04SB2-0055
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
6 Skyline Drive, Hawthorne, NY, 10532
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
796359289
Principal Investigator:
Shyam Raghunandan
Director of Engineering
(914) 345-2442
shyamr@anvik.com
Business Contact:
Kanti Jain
President
(914) 345-2442
kjain@anvik.com
Research Institute:
n/a
Abstract
The ability to efficiently utilize the large surface area of entities such as buildings, tanks, and ships as active, intelligent skins will allow these assets to become part of a larger, highly-responsive, complex nervous system in mission critical scenarios. This will enable information that would otherwise not be available for real-time monitoring and response. Large-area assets would also allow efficient harvesting of lost energy and a feedback to the original system, leading to significant energy and cost savings. One of the key limitations to this advance has been the lack of large-area manufacturing and integration capability that would best utilize the enormous potential of such systems. In this proposal, we will develop a large-area, intelligent, composite-matrix sensor network using a combination of reinforced woven fabric, and microelectronic processing technologies. In the Phase I program, we will develop a design of the composite-matrix sensor structure and validate the process and equipment to enable scaling to large areas. In the follow on Phase II program, we will demonstrate a large-area sensor network in collaboration with an end-user, and demonstrate a functional product. We will commercialize the final product and offer it to the military and commercial markets in Phase III.

* information listed above is at the time of submission.

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