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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

Displaying 1 - 10 of 4139 results
  1. Awayr Security: Validating the NIST Phish Scale Toward Artificial Intelligence Approaches Toward Human Cybersecurity

    SBC: Awayr, Inc            Topic: 90

    Remote operated social engineering (ROSE) attacks account for a surprising share of successful cyberattack. For example, The Verizon Data Breach Incident Response 2019 report found that approximately 94% of all malicious code was introduced into systems via email. Threat actors, illegally, benefit from knowledge gained from repeated massive remote operated social engineering operations. Defensive ...

    SBIR Phase I 2020 Department of CommerceNational Institute of Standards and Technology
  2. An Integrated Data System for Machine Learning based Prediction of Radio Frequency Integrated Circuits (RFIC)

    SBC: HelloMaxwell, Inc.            Topic: 90

    Radio frequency integrated circuits (RFICs) are key components for wireless communication system. RFIC’s hard-tomodel parasitic effects and poor simulation accuracy require multiple trial-and-error tape-outs (fabrications) to meet product specs. Tape-out is very slow (2 months) and very costly (as high as $2M). In the coming 5G era, this problem gets worse as mmWave frequency parasitic effects a ...

    SBIR Phase I 2020 Department of CommerceNational Institute of Standards and Technology
  3. Direct Performance Evaluation of Additive Manufacturing Process Plans

    SBC: INTACT SOLUTIONS INC.            Topic: 90

    Additive manufacturing is steadily advancing towards fulfilling its promise of customized and on-demand production of functional parts. However, performance of as-manufactured parts can differ significantly from the as-designed parts because the as-manufactured geometry differs from the as-designed geometry and the as-manufactured material properties are unknown. Attempts to predict performance of ...

    SBIR Phase II 2020 Department of CommerceNational Institute of Standards and Technology
  4. 8-Predictive Analytics for Normalcy Reasoning and Anomaly Analysis (8-PANORAMA)

    SBC: Boston Fusion Corp.            Topic: N193A01

    Predictive Analytics for NOrmalcy Reasoning and AnoMaly Analysis (PANORAMA) is a machine learning (ML) tool for automatic identification system (AIS) data that learns maritime patterns of life and detects anomalous vessel behavior. PANORAMA learns what is normal for a given ship, taking into account: (1) that ship’s past behavior, (2) the past behavior of similar ships, (3) normalcy patterns in ...

    SBIR Phase I 2020 Department of DefenseNavy
  5. Focus Area 8- (SPADE) Spatial Anomaly Detection

    SBC: Aptima, Inc.            Topic: N193A01

    Coastal and marine navigation, as well as doing so safely, requires the correct identification of vessel type and prediction of behaviors. While the development of Automatic Identification System (AIS) has eased the burden of vessel localization and identification, errors still occur due to improperly configured messages, whether done innocently or maliciously.In order to increase the safety of ou ...

    SBIR Phase I 2020 Department of DefenseNavy

    SBC: TAGUP INC            Topic: N193A01

    Current USMC logistics information systems do not possess the predictive modeling and simulation tools required to support strategic mission critical MAGTF planning efforts. Standard maintenance and supply information (service requests, spare parts requisitions, NIIN inventories, fleet readiness metrics, etc.) is readily available in an ERP system and is visualized via custom-built asset health/fl ...

    SBIR Phase I 2020 Department of DefenseNavy
  7. (1)- Actionable Analytics Using AI/ML for Supply and Sustainment Mission Success

    SBC: Beacon Interactive Systems LLC            Topic: N193A01

    For N193-A01, Beacon is proposing to develop innovative AI and ML technologies that can predict and prescribe items for resupply within Naval Air Operations. The approach will be to build upon previous successful SBIR transitioned shipboard digital assets. The innovation proposed is to use AI / ML to inform and provide actionable intelligence into the supply chain from the operational point-of-per ...

    SBIR Phase I 2020 Department of DefenseNavy
  8. 2- AI Naval Inter-domain Tracking and Recognition Onboard Unmanned System (AI-NITROUS)


    The Navy needs automated ways to be able to understand the air, land, surface and subsurface surroundings of its unmanned systems based on sensor data. ASRI’s goal for this research effort is to expand the capability for the Navy’s unmanned aerial systems (UAS) to monitor, detect, track and classify relevant targets simultaneously in land, surface, and subsurface domains. ASRI’s solution wil ...

    SBIR Phase I 2020 Department of DefenseNavy
  9. 1- STORMY: Storm-Aware USV Operations using Multi-Objective Autonomy

    SBC: Scientific Systems Company Inc.            Topic: N193A02

    STORMY (Storm-Aware USV Operations using Multi-Objective Autonomy) will allow a USV to weigh global mission objectives such as arrivals at a time-prioritized sequence of locations against damage to the vessel due to high seas or collision with other vessels during long-duration missions. The proposed WAVES technology addresses these issues with a two-tiered approach to vehicle motion which conside ...

    SBIR Phase I 2020 Department of DefenseNavy
  10. (2) Adaptive Perception Behaviors (APB)

    SBC: Charles River Analytics, Inc.            Topic: N193A02

    To be mission-relevant, Navy unmanned surface vehicles (USVs) must perceive and behave like manned ships. Cameras are valuable for supporting human-like perception because their high-resolution detail enables ship classification, tracking, COLREGS determination, and threat characterization. Human watchstanders use a variety of cues and heuristics to scan the surroundings and contacts optimally, bu ...

    SBIR Phase I 2020 Department of DefenseNavy
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