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Award Data

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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. Handheld Hidden Chamber Detection

    SBC: TIALINX, INC.            Topic: SOCOM173004

    SOCOM requires rapid implementation and delivery of a handheld, automated hidden chamber sensor system to detect, locate, and discriminate hidden compartments. TiaLinxs Eagle-NC is a wall imager that operates as an ultra-wideband (UWB) radio frequency (RF) sensor integrated with advanced computer vision algorithms, state-of-the-art computer processor technologies, and has a fully integrated displa ...

    SBIR Phase I 2018 Department of DefenseSpecial Operations Command
  2. SUAS Killer, Identifier, and Tracker

    SBC: Physical Optics Corporation            Topic: SOCOM173005

    To address USSOCOMs need for a system to detect, locate, track, and either disable and/or destroy a small unmanned aerial system (SUAS) from a distance, Physical Optics Corporation (POC) proposes to develop the new SUAS Killer, Identifier, and Tracker (SKEET) system. The SKEET system is based on a new design that combines state-of-the-art airspace monitoring technology utilizing compact scanning r ...

    SBIR Phase I 2018 Department of DefenseSpecial Operations Command
  3. Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia

    SBC: HVMN Inc.            Topic: SOCOM17C001

    In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  4. Bilayer Nanofibers as Wearable Sensors for Detecting Fentanyl Compounds

    SBC: Vaporsens, Inc.            Topic: HSB0181001

    Drug overdose is now the leading cause of death for Americans under 50 years old, with fentanyl claiming more lives than any other drug.Alarmingly, the problem is increasing, with fentanyl overdoses claiming nearly twice as many lives in 2016 compared to 2015.In addition to users, first responders are at risk for coming into contact with fentanyl as they perform their duties.Fentanyl is extremely ...

    SBIR Phase I 2018 Department of Homeland Security
  5. Miniature Intelligent Spectral Analyzer

    SBC: Physical Optics Corporation            Topic: HSB0181003

    To address the DHS need to rapidly detect radio interference of critical radio frequency (RF) communications channels utilized by first responders, Physical Optics Corporation (POC) proposes to develop a new Miniature Intelligent Spectral Analyzer (MISCAN) device based on a combination of commercial off-the-shelf (COTS) electronic components in a custom software-defined configuration along with in ...

    SBIR Phase I 2018 Department of Homeland Security
  6. Automated and Scalable Analysis of Mobile and IoT Device Firmware

    SBC: RAM LABORATORIES            Topic: HSB0181008

    As Internet of Things (IoT) and mobile devices become increasingly popular and widely used, the security of the firmware running on these devices is paramount.However, due to the lack of an efficient and scalable analysis framework, combined with the increasing pressure to get products to market as quickly as possible, the software running on these devices is never properly checked for security vu ...

    SBIR Phase I 2018 Department of Homeland Security
  7. Advanced Receiver for Distressed Emitter Localization (ARDEL)

    SBC: TOYON RESEARCH CORPORATION            Topic: HSB0181002

    A majority of U.S. adults own a cell phone and are inclined to use it in emergency situations to call for assistance. Unfortunately, in areas where the density of cell towers is low, such as in rural and off-shore environments, the ability of the wireless network to geolocate the origin of the wireless signal is poor to non-existent. Under the proposed effort, Toyon Research Corporation will devel ...

    SBIR Phase I 2018 Department of Homeland Security
  8. Remote Phone Locator for Improved Emergency Rescue

    SBC: Physical Optics Corporation            Topic: HSB0181002

    To address the Department of Homeland Security (DHS) need for a cell phone location finder for maritime and remote search and rescue (SAR), Physical Optics Corporation (POC) proposes to develop a new REmote Phone Locator for Improved Emergency Rescue (REPLIER). REPLIER leverages novel techniques recently developed at POC to extend the range of cellular communications and integrate commercial cellu ...

    SBIR Phase I 2018 Department of Homeland Security
  9. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  10. Low-Shot Detection in Remote Sensing Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA172002

    Toyon Research Corporation proposes to research and develop algorithms for low-shot object detection, adapting popular techniques to address the complexities inherent in ATR for remote sensing. Traditional object detection algorithms rely on large corpora of data which may not be available for more exotic targets (such as foreign military assets), and therefore, traditional Convolutional Neural Ne ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
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