Abstracts of DHS SBIR-2011.2 Phase II Awards
Back to Award List



Signal Systems Corporation
877 Baltimore Annapolis Blvd.
Suite 210
Severna Park, MD 21146-4716

Proposal Information DHS SBIR-2011.2-H-SB011.2-001-0007-II - Three Dimensional Acoustic Sensing Unit (3DASU) Phase II
Topic Information H-SB011.2-001 - Low Power Tri-axial Acoustic Sensor
Award/Contract Number D13PC00005

SSC proposes a low power tri-axial acoustic sensor that leverages our existing acoustic chambered design to provide a directional sensor that has high sensitivity, rugged construction with low power consumption. Our approach extends prototypes developed under DoD sponsorship, including DARPA, Army, Navy and Special Forces efforts. Our innovative chambered design provides a large physical aperture that includes novel wind noise reduction features without exposing sensitive microphone elements to the environment directly. The unit exhibits increasing acoustic gain at higher frequencies that help in classification of targets that have weak high frequency signature information.

Back to top



35 Hartwell Avenue
Lexington, MA 02421-3102

Proposal Information DHS SBIR-2011.2-H-SB011.2-002-0006-II - Development of a New Collection Methodology for Low Volatility Chemicals from Porous Surfaces
Topic Information H-SB011.2-002 - Improved Wipes for Surface Sampling of Chemical Agents on Porous Materials
Award/Contract Number D12PC00473

In this effort, TIAX LLC will complete development of an innovative combination of commercially available materials that will permit the efficient and reproducible extraction, collection, concentration, recovery and analysis of low volatility chemicals from porous surfaces such as concrete, painted wall board, and flooring tiles. This work builds on a successful Phase I program, that demonstrated a proprietary method that collects significantly higher amounts of target compounds when compared to a standard collection method. Those higher comparative yields were up to 50 times greater than the standard method that utilizes gauze wipes with a solvent. The successful development and evaluation of this new surface collection methodology will yield a new SOP for the sampling and analysis of surfaces that have been contaminated by low volatility organic chemicals. After a chemical contamination event, the results obtained from this approach can be used for subsequent legal proceedings and also to verify the effectiveness decontamination procedures on porous surfaces. The fully developed method will have commercial uses in the analysis of low volatility chemicals, and as such a wide market potential for use in both environmental contamination and forensic applications. This Phase II effort will allow this methodology to proceed through a Technology Readiness Level (TRL) of 5 "Component and/or breadboard validation in a relevant environment". If exercised, the proposed two Option Years will then result in a TRL level of 7, "System prototype demonstration in an operational environment".

Back to top



1000 Lake Street
Suite 203
Oak Park, IL 60301-1131

Proposal Information DHS SBIR-2011.2-H-SB011.2-003-0006-II - Sub-topic 1. NAND/NOR Chip Forensics - Phase II
Topic Information H-SB011.2-003 - Mobile Device Forensics
Award/Contract Number D12PC00474

The overall goal of this project is to develop new tools and techniques to address current limitations in mobile forensics. Many factors, including NAND Flash memory, passcode protected phones, encrypted data, lack of device support and simplistic analysis techniques in current forensic tools drive the need for advancements in mobile forensic tools. Phase I of this project was highly successful. We developed techniques that created a forensically sound and verifiable image of data on devices utilizing NAND flash memory. We also developed tools which enabled more effective analysis of the acquired data. Phase II will build upon the successes of Phase I by: 1. Expanding the number of Android devices our NAND Flash Write Blocker (vNandBlock) and acquisition tools support; 2. Porting applicable vNandBlock and acquisition tools Apple iOS and Windows Phone devices; 3. Applying advanced analytic techniques to extract mobile forensics data; 4. Developing forensic training modules which incorporate the knowledge gained in the development of these new techniques and tools. The new tools and techniques developed in Phase II would provide direct benefit to law enforcement agencies tasked with analyzing mobile devices in civil, criminal and national security investigations. The advanced data analysis engine would greatly improve the amount of intelligence which could be generated from mobile devices. viaForensics believes that Phase II will enable us to expound on our existing and proven commercialization vehicles including viaExtract(TM) (our forensic software product) and proprietary training courses and aggressively pursue opportunities to license our technology to other commercial entities.

Back to top



Alakai Defense Systems, Inc
7935 114th Ave N
Suite 1100
Largo, FL 33773-5028

Proposal Information DHS SBIR-2011.2-H-SB011.2-004-0004-II - Standoff Explosive Raman AIT Upgrade Module
Topic Information H-SB011.2-004 - Short Standoff Checkpoint Detection Systems for Explosives
Award/Contract Number D12PC00494

Alakai proposes to develop a Standoff Explosive Raman AIT Upgrade Module (SERAUM) which utilizes, Eye-safe, deep UV Raman scanning/imager to detect explosives and their precursors, for short standoff trace explosive detection. This system is designed for integration into DHS's Advanced Imaging Technology (AIT) systems to provide a chemical signature of explosives thereby improving the screening effectiveness of personnel and baggage. Alakai is a leader in Standoff UV Raman for DoD applications, as evidenced by being the first known company to undergo an Army technical, operational and human factors evaluation of their standoff checkpoint explosive detection system, along with a safety release for use by soldiers. Alakai can leverage its existing UV Raman capability (proven hardware performance, existing UV Raman library and detection algorithm) to customize a completely eye-safe UV Raman system for TSA screening applications. In Phase I Alakai demonstrated standoff detection of finger print quantities of 10 different explosives and Homemade Explosives (HMEs) at 25cm range and a subset of these compounds at 50cm range. The Phase II project will integrate the UV Raman scanning technology into an L-3 ProVision(R) AIT for further demonstration of the combined scanning technology.

Back to top



Neya Systems, LLC (formerly Rhobotika, LLC)
145 Pine Rd
Evans City, PA 16033-3323

Proposal Information DHS SBIR-2011.2-H-SB011.2-005-0011-II - A Machine Learning Tool for Image Quality Assessment through Prediction of Iris Recognition Success
Topic Information H-SB011.2-005 - Iris Image Quality Tool Suite for Biometric Recognition
Award/Contract Number D12PC00477

In Phase I we developed a machine learning method for predicting match score errors in iris imagery to determine the quality of the image. We now propose to develop a flexible and configurable tool for creating, refining, and applying such a match score predictor to any image quality assessment problem where a training signal can be identified. The tool will enable users to supply ground truth for image labeling through an intuitive plugin. It will provide a set of feature plugins for feature extraction while allowing users to add their own. It will provide users with access to the training process for the image quality assessment through a training plugin. It will offer automatic feature selection to reduce the feature set to the most efficacious through a feature selection plugin. And it will provide extensive analysis capabilities to determine the effectiveness of the image quality assessor on test data. Scripting support will allow the user to invoke our algorithms without need for the GUI if desired. Such a flexible image quality assessment system will have application beyond iris recognition to other areas in biometrics, such as face recognition, but also to domains such as stereovision, visual odometry, and general object recognition. Our work will take this technology to TRL 4 toward TRL 5 through integration of commercial segmentation software, testing on realistic data, and interfacing with an iris imager to simulate the target environment.

Back to top



Physical Optics Corporation
1845 West 205th Street
Torrance, CA 90501-1510

Proposal Information DHS SBIR-2011.2-H-SB011.2-006-0020-II - Web-based Intelligent Extraction of Symbology based on Contextual Information
Topic Information H-SB011.2-006 - Intelligent 'Object' Symbology
Award/Contract Number D12PC00475

To address the DHS need for intelligent symbology technologies, Physical Optics Corporation (POC) proposes to continue the development of Web-based Intelligent Symbology Extraction based on Context (WISEC), a unique enterprise symbology system that integrates state-of-the-art natural language processing (NLP) tools with our syntactic event attribute extraction and contextual event coreference algorithms. In Phase I, we demonstrated the feasibility and maturity of WISEC by developing its design and software prototype for incident management and crime information sharing applications, with mature functionalities (automatic symbol generation using open-source unstructured data, association of events from multiple sources, dynamic event status update, and platform-independent user interfaces for review and information "drill down"). In Phase II we will extend this software prototype in functionality, performance, and maintenance into a mature enterprise software system, test it with both DHS and local users, evaluate its performance in classification, coreference, and scalability, and deliver it to the DHS. The successful completion of this project at the end of Phase III will benefit the nation in both government and commercial sectors by providing intelligent symbology with standard representation that is sharable among various communities. Commercial applications for this technology include business intelligence, text analytics, and enterprise content management and archiving.

Back to top
Back to Award List