Army RCCTO: Sensor Synthetic Data Generation

Due Date: Nov 30, 2021 12:00 pm EST Government Organization: Army Rapid Capabilities and Critical Technologies Office (RCCTO) Description: On October 12, the U.S. Army posted an applied small business innovation research (SBIR) announcement. Proposals are due by 12:00 p.m. Eastern on November 30. The US Army requires large-scale, accurate, easily accessible training, test, and validation data to support AI model development for multiple security domains

Category: Opportunity

DoD Communities Of Interest: Artificial Intelligence

Subject: Sensor Synthetic Data Generation

Due Date: Nov 30, 2021 12:00 pm EST

Government Organization: Army Rapid Capabilities and Critical Technologies Office (RCCTO)

Description :

On October 12, the U.S. Army posted an applied small business innovation research (SBIR) announcement. Proposals are due by 12:00 p.m. Eastern on November 30.

The US Army requires large-scale, accurate, easily accessible training, test, and validation data to support AI model development for multiple security domains (e.g., SIPR, JWICS…). Sensor data is critical to developing AI/ML models. Unfortunately, there is not enough data yet to create highly performant models. Sensor Synthetic Data Generation will potentially reduce the bottleneck of training data supply that helps improve ML models by developing a synthetic data generation tool.

Currently, nearly all of the AI/ML models are developed using actual or representative data. There is not enough unique defense/intel data to create performant models (e.g., it takes roughly 50M pieces of data to create a 60-70% performant model). Additionally, this data must be labeled; synthetically generated data can be labeled as generated, reducing human data labeling effort for real-world data and data generated from an external (e.g., vendor) source.

Sensor Synthetic Data Generation topic encompasses the development of a synthetic data generation tool for sensors (e.g., radar, etc.) that can augment the limited, labeled training data available to support Artificial Intelligence / Machine Learning model development. The purpose of this topic is to lead to the creation/integration of mission-focused synthetic data to include but not be limited to Priority Needs: Commercial Satellites/Electro-Optical (EO) – World View 1,2,3 (Imagery), Digital Globe, Blacksky // Synthetic Aperture Radar (SAR) – RADARSAT and Capella; Other Needs: 0903 Full Motion Video (FMV) // Electronic Intelligence (ELINT) spectrums/waveforms // Variable Message Format (VMF) and Chat; Desired synthetic data to be used in AI/ML model development: Surface to Surface Radars, Surface to Air Missile Launchers, Tanks, Etc.

Website: https://sam.gov/opp/6ffab77460f64eaab331b67a89f2e9d9/view

Questions or assistance, contact:
North Carolina Defense Technology Transition Office (DEFTECH)

 

Dennis Lewis
lewisd@ncmbc.us
703-217-3127

Bob Burton
burtonr@ncmbc.us
910-824-9609

North Carolina Defense Technology Transition Office | PO Box 1748, Fayetteville, NC 2B303