SBIR/STTR Research Award

An Autonomous Severe Weather Trend Monitor for Improved System-Wide TFM Execution

Award identifier 074e9e1655a2ce4b41daa72c64364bffd1de4682805e9bdcf8b41b1b66e15f4cAwarding agency National Aeronautics and Space Administration

Award amount

$124,918

Program and phase

SBIR · Phase I

Award year

2020

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 Aeronautics and Space Administration
Branch
Not reported
Recipient company
AvMet Applications, Inc.
Proposal award date
2020-08-28
Contract end date
2021-03-01
UEI
JM2UEBH19NN5
Solicitation number
SBIR_20_P1
Topic code
A3

Research abstract

Severe weather remains the main disruptor to airspace operations and traffic managersrsquo; actions. An autonomous airspace system will need to automatically ingest the latest weather forecast(s), reason about its impact, and provide actionable guidance to human operators (in the transition) and/or other service-based airspace automation systems. Our proposed Innovation lays the foundation for such automated weather reasoning and focuses on a specific aspect of autonomous operation with clearly stated practical needsmdash;TMI impact reductionmdash;to demonstrate its capabilities.Todayrsquo;s manually executed TMIs are often overly restrictive, and once activated are not routinely reviewed for possible reduction in scope or duration resulting in excess delays amp; costs. We propose an autonomous system which will monitor the latest weather, traffic, implemented TMIs, and look for opportunities to reduce their impact on the NAS. The application will:Continuously ingest latest NOAA weather forecasts, air traffic, and TMI information from FAA SWIM feedPerform automated Forecast Trend Analysis to compare the latest information to previous forecast(s) and NAS status, and identify when an in-depth search for TMI reduction is warranted, e.g., when forecasts evolve toward less-severeIf warranted, run a set of parallel fast-time simulations starting from current NAS status and extending up to 6-8 hours ahead, combining two ldquo;what-ifrdquo; series of experiments:Meteorologically sound range of alternative weather scenario outcomes representing the underlying forecast uncertaintyParameterized TMI reductions in scope and end timesEvaluate results (including comparison with the outcomes of previous cycles) to establish, with a required degree of confidence, if a non-trivial and specific TMI reduction opportunity existsAlert relevant traffic managers for review and actionContinue autonomously monitoring and looking for additional TMI reduction opportunities throughout the operational day

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

6 SBIR/STTR records share this UEI (2016–2023). Reported award amounts total $1,402,603. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: National Aeronautics and Space Administration

Agency intelligence

National Aeronautics and Space Administration

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.