Award Data

The Synthetik team is pleased to provide this Phase I SBIR proposal to develop a distributed, interoperable, ISO 18013-5-compliant and mdoc-based digital software badge (DSB). The DSB will provide the capability to prove a first responder personnel’s identity and qualifications onsite securely and efficiently in a disaster response operating environment.During Phase I we will demonstrate th ...

Modern lithium ion batteries are known for their poor safety performance, with many reports of battery failure and fire having been reported. One of the major causes of battery fire is from the use of flammable solvents, such as organic carbonates, as the electrolyte. These hazards have long limited the usage of batteries in dangerous conditions, such as on the battlefield. To combat this issue, t ...

Modern lithium ion batteries are known for their poor safety performance, with many reports of battery failure and fire having been reported. One of the major causes of battery fire is from the use of flammable solvents, such as organic carbonates, as the electrolyte. These hazards have long limited the usage of batteries in dangerous conditions, such as on the battlefield. To combat this issue, f ...

This SBIR effort proposes using live and continuous monitoring of metal tanks, pressure vessels, and pipelines using carbon nanomaterial-based sensing skins to detect excessive physical strains, cracks, and to inspect impact damage. The proposed research and development work leverages 15+ years of fundamental research. The key objective is to advance the TRL level and the scalability of carbon nan ...

The Synthetik team is uniquely placed to conduct this Phase II SBIR effort where we plan to extend and optimize our DeepSpektra high-resolution hyperspectral and deep learning-based non-contact detection technology to provide enhanced, targeted sampling for explosive and illegal drugs trace detection that was successfully demonstrated in Phase I.Synthetik's DeepSpektra technology directly addresse ...

As sensing, computing, and computational imaging technology advances, it becomes more feasible to integrate them into tightly coupled and fully featured solutions in minimal size, weight, and power – cost (SWaP-C) form factors. In this project, we will develop a camera system for use in a variety of scenarios, from surveillance to targeting systems. Our focus will be building a computational ima ...

Deep learning offers a powerful and extensible toolset to achieve or perhaps even exceed human-level accuracy for automatic object detection in stream of commerce data, and offers a path toward improving the effectiveness of scanners, reducing wait times, and radically increasing the accuracy of screening, where automatic object detection support is essential. A deep learning-based system for auto ...

Currently fielded aviation passenger screening systems are large, fixed systems capable of detecting concealed objects on a person. While this approach is useful for standard passenger screening, there are additional requirements for a handheld system to enable concepts of operations that the fixed systems canNt accommodate.Previous systems have tended to be passive systems that lack the resolutio ...

Synthetik propose to leverage a new generation of high-resolution, low-cost (e.g. less than $1,000, 25-100x less than currently available systems) hyperspectral cameras in conjunction with state-of-the-art machine learning to rapidly image, process and predict locations where residues of interest are present to deliver a targeted, relevant and more dense samples to the trace detector.During Phase ...

Deep learning offers a powerful and extensible toolset to achieve or exceed human-level accuracy for automatic object detection in stream of commerce data. However, in order to train deep machine learning-models for 2D and 3D screening a significant quantity of high-quality ground-truth training data is required.We propose SoCPhysics: A Stream-of-Commerce Physics-Based Data Generation Application, ...