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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.

  1. Learning traffic camera locations using vehicle re-identification

    SBC: Arete Associates            Topic: NGA201005

    In its effort to provide necessary intelligence and analysis, the National Geospatial-Intelligence Agency (NGA) utilizes extensive traffic camera systems. However, the large amount of data overwhelms both analysts and existing processing methods. In order to provide a better understanding and reduce the search space for common problems such as target tracking, it is necessary to extract the camera ...

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  2. Vehicle Reidentification-Aided Network Topology Inference (VRANTI)

    SBC: Systems & Technology Research LLC            Topic: NGA201005

    Systems & Technology Research (STR) proposes to develop Vehicle Reidentification-Aided Network Topology Inference (VRANTI), a novel system for estimating proximity network graphs of traffic cameras to facilitate intelligence applications such as tracking and monitoring of traffic systems. Network inference will be performed using statistical analyses of features extracted from camera video feeds, ...

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  3. SHAPE-BASED GENERALIZATION BOUNDS FOR DEEP LEARNING

    SBC: GEOMETRIC DATA ANALYTICS INC.            Topic: NGA20A001

    We propose to develop a theoretical understanding of the relationship between intrinsic geometric structure in both training and latent data and characteristics of functions learned from that data for deep neural network (DNN) architectures. Along the way we propose to also understand the structure of the neural networks that are best trained on a given data set. Both of these theories will lead t ...

    STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  4. Bounding generalization risk for Deep Neural Networks

    SBC: Euler Scientific            Topic: NGA20A001

    Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels.  In an ...

    STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  5. Automating tilt and roll in ground-based photos and video frames

    SBC: INTERNATIONAL ASSOCIATION OF VIRTUAL ORGANIZATIONS, INCORPORATED            Topic: NGA201006

    NGA seeks an innovation to fully automate processes that recover camera orientation parameters, specifically for ground-based “photo” (aka image) and video frame use cases. The ability to use these ground-based systems represents an enhanced aspect to traditional photogrammetry, and in many regards, folding in hand-held systems, and considering the nuances associated with these collects, is ye ...

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  6. Monitoring and Inspecting Dirty Nukes Including Generating Heatmaps of Terrain (MIDNIGHT)

    SBC: CHARLES RIVER ANALYTICS, INC.            Topic: HSB0191010

    A successful WMD terrorist attack against the United States would have profound and potentially catastrophic impact on our nation. Quick, efficient, and effective localization of radiological threats in unstructured environments is imperative to mitigate and deny such an event. Man-portable devices are used to localize radiological materials in unstructured environments, but manned detection is bo ...

    SBIR Phase II 2020 Department of Homeland SecurityCountering Weapons of Mass Destruction
  7. Dynamical Network Models for Holistic Risk Management in Next-Generation 911 Systems

    SBC: Achilles Heel Technologies, Inc            Topic: HSB0191007

    The Next-Generation 911 (NG911) initiative, which aims to update the United States' emergency communications systems to be Internet Protocol-based, should bring about profound benefits in system usability and resilience. However, there is great concern that NG911 systems will be highly vulnerable to cyber- risks, both because the increased accessibility provided by the system increases likelihood ...

    SBIR Phase II 2020 Department of Homeland Security
  8. Hybrid Machine Learning Approaches for Radiation Signature Identification

    SBC: RADIATION MONITORING DEVICES, INC.            Topic: NGA192002

    To improve the identification and detection of radio-logical materials, we propose a hybrid supervised learning and unsupervised machine learning approach to reduce the false positive rate, increase the accuracy and throughput, and augment the capabilities of the human operators. At the end of the Phase I, we will have a machine learning algorithm that is trained to recognize a variety of nuclear ...

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  9. Cybersecurity Peer-to-Peer KNwledge/Lessons Learned Tool

    SBC: INFERLINK CORP            Topic: HSB0191006

    The increasing number of breaches and hacks against organizations demands new and more effective ways to provide defense. Increased kNwledge sharing among peers could make a tremendous difference in improving current practices, especially since the cyber landscape is a dynamically changing environment. Our goal is to develop an effective peer-to-peer platform for sharing cybersecurity kNwledge and ...

    SBIR Phase II 2020 Department of Homeland Security
  10. Automated Assessment of Urban Environment Degradation for Disaster Relief and Reconstruction

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA181004

    Toyon Research Corp. proposes development of a software prototype for automated 3D damage assessment in urban environments. We will document the requirements for the algorithms and software, and optimize or extend the algorithms as needed. We will implement the software prototype, leveraging and integrating existing components where possible and implementing new components as needed. We will qua ...

    SBIR Phase II 2020 Department of DefenseNational Geospatial-Intelligence Agency
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