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Award Data
The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.
Download all SBIR.gov award data either with award abstracts (290MB)
or without award abstracts (65MB).
A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.
The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.
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Automated Driving Systems (ADS) Test Data Interface
SBC: Sea, Ltd. Topic: 190NH1SEA is proposing a technical evaluation and feasibility study for a Test Data Interface that could send command signals to a vehicle via CAN, as well as receive diagnostic information from the vehicle. This technology could be used to provide any number of vehicle test protocols, including the evaluation of advanced and autonomous driving features.SEA believes that a Test Data Interface will be a ...
SBIR Phase I 2020 Department of Transportation -
RLS & Associates, Inc. 190-FT1 Submission
SBC: RLS & Associates, Inc. Topic: 190FT1In the passage of the Fixing America's Surface Transportation Act (Pub. L. No. 114-94), Congress challenged the U.S. DOT and the Federal Coordinating Council on Access and Mobility (CCAM) to develop a cost allocation technology to account for disparate federal reporting requirements and maintain separation of funding sources by trip for non-emergency medical transportation. The U.S. DOT notes the ...
SBIR Phase I 2020 Department of Transportation -
Demonstration of a Drone-Based Track Safety Inspection System Using Asset-Based Change Detection
SBC: Noble Drone Services, LLC Topic: 180FR4Today’s prevailing methods of visual track inspection tend to be expensive, disruptive to operations, and have potential to be less thorough than preferred. To help address these issues, machine vision technology emerged in the rail sector over a decade ago; however, the technology has not achieved its expected potential due to the uncontrolled nature of rail environments. Recent findings have s ...
SBIR Phase II 2020 Department of Transportation -
NDT of Fracture Toughness for Pipeline Steels
SBC: FBS INC Topic: 180PH1Fracture toughness is the material parameter that, along with applied loading and flaw geometry, dictates the critical crack size, and therefore controls the flaw size that must be detected during inspections. A major challenge facing pipeline operators is that many pipelines are old, making their structural integrity uncertain, and that material pedigree of the pipeline steel is unknown. Therefor ...
SBIR Phase II 2020 Department of Transportation -
Ship-based Operations for UAS Swarms with Autonomous Pinniped Homing Over Nasty Environments (SOUSAPHONE)
SBC: CHARLES RIVER ANALYTICS, INC. Topic: 9501Small Unmanned aircraft systems (UAS) play a critical and growing role in government, military, commercial, and scientific operations across a range of missions such as weather monitoring, natural disaster assessment, surveillance, and infrastructure inspection. Their versatility, maneuverability, and dependability, coupled with their ability to keep operators out of harm’s way, make them critic ...
SBIR Phase I 2020 Department of CommerceNational Oceanic and Atmospheric Administration -
DeepCTIS: A New Low-Cost Hyperspectrual Imaging Module and Distributed Deep Learning Platform to Combat Illegal, Unreported, and Unregulated Fishing in the Marketplace at Scale
SBC: SYNTHETIK APPLIED TECHNOLOGIES LLC Topic: 9202We propose an innovative yet straightforward approach to developing and delivering a readily deployable product to support combating IUU. We combine newly available low-cost hyperspectral sensors with state-of-the-art deep learning-based real-time data processing and deploy it on high-availability commodity cloud computing hardware - our solution is compatible with both existing systems as well as ...
SBIR Phase I 2020 Department of CommerceNational Oceanic and Atmospheric Administration -
Small Satellite Cloud Observation System
SBC: ATMOSPHERIC & SPACE TECHNOLOGY RESEARCH ASSOCIATES LLC Topic: 9601We propose the design of an optical instrument package capable of making cloud observations and deployable on a CubeSat. The design will be based on decades of research in cloud remote sensing and each spectral channel will be comprised of a commercial-off-the-shelf camera and a spectral filter as needed. The base design will be comprised of three channels, two in the shortwave infrared and one in ...
SBIR Phase I 2020 Department of CommerceNational Oceanic and Atmospheric Administration -
Biomimetic Adhesives for Restoration of Coral Reefs
SBC: WARDENCLYFFE CHEMICALS, INC. Topic: 9201Restoration of coral reefs is dependent upon an ability to adhere young corals, grown in tanks, onto inorganic substrates within the seas. The epoxies in current use do not provide a viable path to restoration owing to poor adhesion underwater, lengthy mixing of components needed, clouds of toxic epoxy precursors released into the water, and extensive diver time needed to clean the underlying cora ...
SBIR Phase I 2020 Department of CommerceNational Oceanic and Atmospheric Administration -
Developing Regional GIC Hazard Tools for Power Utility Planning and Operations
SBC: COMPUTATIONAL PHYSICS, INC. Topic: 9302Geomagnetically induced current (GIC) hazard is a recognized threat to the United States power system. Federal models to support hazard specification and prediction for critical infrastructure are at an advanced state, including models of space weather, the Earth’s conductive structure, and regional geoelectric field. We propose to use existing NOAA Space Weather Prediction Center (NOAA-SWPC) mo ...
SBIR Phase I 2020 Department of CommerceNational Oceanic and Atmospheric Administration -
Enabling the Rapid Creation of Custom Predictive Models with GOES-16 and NEXRAD Data
SBC: ONAI INC. Topic: 9401NOAA's Big Data Project (BDP) has made several valuable datasets available on major cloud platforms. While a critical step, many organizations that would benefit from the data are not technologically capable of performing state-of-the-art machine learning. We propose to unlock the power of the data for those who can most benefit by developing technology that automatically trains deep learning mode ...
SBIR Phase I 2020 Department of CommerceNational Oceanic and Atmospheric Administration