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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. STEWARD: Sensor Technologies for Enhancing Workplace Awareness through Remote Discernment

    SBC: APTIMA INC            Topic: DLA162001

    Warehouse injuries and accidents are occurring much too frequently and resulting in devastating consequences and implications for the involved facility. Although the recent emergence of low-cost and unobtrusive sensor technologies have flooded nearly every market to improve health and safety, the warehousing and manufacturing markets have remained largely unpenetrated. Aptima plans to fill this ga ...

    SBIR Phase I 2017 Department of DefenseDefense Logistics Agency
  2. The Property Reuse and Disposition Tool

    SBC: Technology Solutions Experts, Inc.            Topic: DLA162003

    Technology Solutions Experts, Inc. (TSE) is proposing to develop the Property Reuse and Disposition Tool, a mobile app that will significantly expedite and facilitate the way in which the Defense Logistics Agency (DLA) catalogs excess property for its reuse.The DLA's current process of cataloging excess property is cumbersome and tedious--with the advent and proliferation of mobile technologies, t ...

    SBIR Phase I 2017 Department of DefenseDefense Logistics Agency
  3. Determining Students' Academic Engagement while Completing Learning Activities and Assessments

    SBC: Tutorgen, Inc.            Topic: edIES15R0005

    With this Phase I funding, the project team will develop and test a prototype of D-TECH, a system to determine students' level of academic engagement while completing computer-based learning activities and assessments. The prototype will integrate within existing third party computer-based programs (e.g., online courseware, educational games, simulations, intelligent tutors) and will consist of a ...

    SBIR Phase I 2017 Department of EducationInstitute of Education Sciences
  4. BATTLE: Battlefield Airmen Training Technologies for LVC, ground-based Environments

    SBC: APTIMA INC            Topic: AF17AT011

    Effective Live, Virtual, and Constructive (LVC) training methods have been underutilized within ground-based training operations. More specifically, Battlefield Airmen training methods have not fully adopted or incorporated recent advances in augmented reality (AR) technologies into their training due to specialized training requirements. To address this issue, the Aptima team will design and deve ...

    STTR Phase I 2017 Department of DefenseAir Force
  5. Target Tracking via Deep Learning

    SBC: Systems & Technology Research LLC            Topic: AF17AT027

    To address the challenge of long-term tracking, through extended occlusions and significant appearance changes, we propose to develop DC-CAT, a Deep Convolutional neural network (CNN) based Confuser-Aware high value target (HVT) Tracker.The DC-CAT system will combine a state-of-the-art CNN-based adaptive HVT tracker with a CNN-based pre-trained generic target detector, in a deep-feature-aided mult ...

    STTR Phase I 2017 Department of DefenseAir Force
  6. Volumetric Diagnostic Imaging of Explosively Driven Fragments

    SBC: RADIATION MONITORING DEVICES, INC.            Topic: AF161003

    ABSTRACT: The size, shape, and velocity distribution of fragments are critical for the complete characterization of high-explosive fragmentation process. Such information is needed for the qualification of new energetic materials as well as for warhead design. Current methods to characterize such fragmentation processes are time consuming because they are performed manually. Such methods are limit ...

    SBIR Phase I 2017 Department of DefenseAir Force
  7. High Speed Plasma Probe and Electronics Suite

    SBC: BUSEK CO., INC.            Topic: AF161004

    ABSTRACT: Busek proposed to develop an instrument package for high fidelity measurements and long-term state-of-health monitoring of plasma properties from solar electric propulsion (SEP) plasma sources in test chambers and the space environment. The proposed system will include a Faraday probe, a Langmuir probe, and an ion energy analyzer. The instrument suite will be capable of periodic, time- ...

    SBIR Phase I 2017 Department of DefenseAir Force
  8. High Confidence, Rapid Alloy Identification

    SBC: JENTEK SENSORS, INC.            Topic: AF161009

    ABSTRACT: The objective of this proposed effort is to develop a procedure that provides high confidence discrimination between (at a minimum) aluminum, titanium and magnesium alloys through dirt, paint and other coatings of interest to the Air Force. The goal is to develop a hand-held alloy identification method that can be performed within a few seconds and one that requires only a few minutes of ...

    SBIR Phase I 2017 Department of DefenseAir Force
  9. User Defined Operational Picture (UDOP) for Enterprise Ground Satellite Command and Control Systems from Multiple Sources

    SBC: SONALYSTS INC            Topic: AF162005

    Sonalysts, Inc. proposes to research and develop a Common User Defined Operational Picture (UDOP) for the Enterprise Ground System (EGS) for satellite Command and Control (C2). We will research and analyze the human factors affecting operator function and performance across multiple satellite systems, and the common and unique aspects of space systems currently in use. We will develop logical cons ...

    SBIR Phase I 2017 Department of DefenseAir Force
  10. Durga- Autonomous Satellite Ground Operations

    SBC: MZEAL COMMUNICATIONS, INC.            Topic: AF162006

    Durga addresses the Air Forces need for Autonomous Satellite Ground Operations using a mature suite of software methods that detect and respond to anomalies in streams of data, both in real time and over history. In addition to detecting rapid spikes or gradual drifts in telemetry data, Durgas methods can discover periodic and seasonal patterns, as well as connections between data features that ca ...

    SBIR Phase I 2017 Department of DefenseAir Force
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