Embedded Structural Platform Analysis Network (eSPAN)TM

Award Information
Agency:
Department of Defense
Branch:
Army
Amount:
$729,916.00
Award Year:
2010
Program:
SBIR
Phase:
Phase II
Contract:
W56HZV-10-C-0138
Agency Tracking Number:
A082-150-0690
Solicitation Year:
2008
Solicitation Topic Code:
A08-150
Solicitation Number:
2008.2
Small Business Information
Impact Technologies, LLC
200 Canal View Blvd, Rochester, NY, 14623
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
073955507
Principal Investigator
 Carl Byington
 Director, Systems Enginee
 (585) 424-1990
 carl.byington@impact-tek.com
Business Contact
 Mark Redding
Title: President
Phone: (585) 424-1990
Email: mark.redding@impact-tek.com
Research Institution
N/A
Abstract
Impact Technologies is creating a low-power, low-cost, and modular wireless sensor network for health and usage monitoring of bridge and vehicle structures. The system utilizes a network of flexible sensor nodes connected to a communication node that transmits high-level health metrics to an external system over a standard vehicle data bus. System intelligence will be distributed among individual nodes to reduce the required communication bandwidth and allow system capabilities to be customized for various structures and vehicle platforms. The system will autonomously generate high-level health metrics without placing a processing burden on existing vehicle management systems. Impact’s Phase II work will focus on maturing a successful Phase I prototype to the point where it’s ready for technology insertion. A prototype sensor network will be designed, built, and installed on representative vehicle and bridge systems. The network will also allow for various combinations of sensors and data reduction algorithms, and will be easily reconfigurable. Ultimately, the goal of Phase II is to produce a transition-ready, mil-grade/ruggedized prototype of a modular smart sensor network that can monitor the condition of structural components on Army vehicles and structures to maximize operational efficiency, increase safety, and provide predictive logistics benefits.

* information listed above is at the time of submission.

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