SBIR/STTR Research Award

STTR Phase I: Towards Command Improvisation Support Systems for Disaster Managers

Award identifier afffd283b5d9c264dd76ae7d986ae4eb39add25249011bf8202efdb562daa47eAwarding agency National Science Foundation

Award amount

$146,689

Program and phase

STTR · Phase I

Award year

2007

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
QUIMBA SOFTWARE, INC.
Proposal award date
Not reported
Contract end date
Not reported
UEI
TCLKSMMQDND5
Solicitation number
NSF 06-553
Topic code
IT

Research abstract

This Small Business Technology Transfer (STTR) Phase I research project will study disaster management from the perspective of agents that are capable of (1) assisting the incident commander in dynamically negotiating between adherence to pre-existing disaster plans and improvisation in the face of unplanned-for situations; and (2) assisting the commander in reconfiguring the command and communication flow to reflect improvisational situations of high complexity. Management of disaster response, in general, closely adheres to prior emergency operations planning, and is executed within the context of a centralized Incident Command System (ICS). Recent research suggests that, in some cases, improvisation - deviation from prior plans or protocols -- may be necessary to achieve optimal performance. However, too much deviation from standard procedure can degrade group situational awareness and overall response effectiveness. An optimal balance between adherence to standard procedure and improvisation exists, and must be negotiated dynamically as the disaster unfolds. Under the pressure of a complex and uncertain disaster situation, it is difficult for a commander to maintain a timely awareness of the situational factors that suggest when a switch away from standard procedure is called for. Hence, agents as described here, are of great value for improving disaster management.The anticipated results of this effort will make a crucial contribution to the training models for disaster response professionals, by providing a framework for the explicit reinforcement of the ability to recognize and act upon situational cues that may call for improvisation. It is envisioned that these training models will ultimately be implemented in an Advanced Distance Learning based simulation that can be easily used for cross-organizational training scenarios.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

7 SBIR/STTR records share this UEI (2002–2008). Reported award amounts total $1,855,136. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Science Foundation, Department of Homeland Security, Department of Transportation

Agency intelligence

National Science Foundation

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.