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DHS S&T PHASE I PROGRAM SOLICITATION FY 13.2

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Agency: Department of Homeland Security
Program/Year: SBIR / 2013
Solicitation Number: HSHQDC-13-R-00032
Release Date: April 2, 2013
Open Date: April 18, 2013
Close Date: May 22, 2013
H-SB013.2-001: Bulk Currency Vapor Detection in Confined Spaces
Description:

Each year, Mexican cartels smuggle approximately $28 to $39 billion from the United States to Mexico through the 417 “official” border crossings between the two countries. Estimates indicate that only 25% to 50% of that money is processed and laundered through financial institutions and instruments other than cash. Congress passed legislation increasing the penalties for smuggling cash out of the United States; however, to many, smuggling cash is a victimless crime and the activity has continued to increase. Existing methods such as stronger operational partnerships, improved intelligence, random vehicle and body searches, and mandatory transaction reporting have helped make some seizures, yet have done little to stem the overall outflow. Department of Homeland Security officials have testified that reducing bulk cash smuggling will disrupt illicit activities and prevent proceeds from funding more crime, thereby reducing cross border violence. The U.S. Customs and Border Protection (CBP) currently does not conduct full-time inspections of outbound traffic, and with a lack of technology deployed at ports of entry, only a fraction of the illicit cash flow is seized. Accurate, fast, non-intrusive methods for detecting smuggled currency at border crossings will complement existing operations and provide the U.S. Immigration and Customs Enforcement (ICE) and CBP with the flexibility to deploy a direct detection capability for immediate results. 

Keywords: Bulk cash, currency detection, Point of Entry (POE), outbound cargo and traffic scanning, vapor sample collection, clutter rejection
H-SB013.2-002: Software Based Roots of Trust for Enhanced Mobile Device Security
Description:

Communication and commerce is shifting to smart phones, tablets and other mobile devices. With this shift, it is important to look at methods for improving the security of these devices and the applications that run on them. This is aided by having a firm foundation from which to build security and trust. Highly trustworthy, tamper evident components, called Roots of Trust (RoTs), that perform vital security functions, can provide this. To support device integrity, isolation, and protected storage, devices should implement the following RoTs:
• Root of Trust for Storage (RTS) - provides a protected repository and a protected interface to store and manage cryptographic keys and other critical security parameters.
• Root of Trust for Verification (RTV) - provides a protected interface and engine to verify digital signatures associated with software/firmware and create assertions based on the result.
• Root of Trust for Integrity (RTI) - provides protected storage, integrity protection, and a protected interface to store and manage assertions.


On laptop and desktop systems, these roots of trust are often provided through a separate chip. This is a challenge on mobile devices where power and space are at a premium. The objective of this SBIR topic is to use software to provide RoTs on commercial mobile devices without the addition of specialized hardware. The software may leverage existing hardware features that have been incorporated into widely available commercial mobile devices. The goal is to provide the security added by ROTs without increasing manufacturing cost. The challenge is offering a level assurance similar to solutions based on specialized hardware. The security functions provided by the ROTs should be made available to the operating systems and applications via an application programming interface. These capabilities would be enhanced by a method for the management and enforcement of policy on the device. 

Keywords: Mobile device, tablet, smart phone, root of trust, device integrity, isolation, protected storage
H-SB013.2-003: Lost Person Locator for First Responders
Description:

Across the United States on any given day there are as many as 100,000 active missing person cases, resulting in thousands of “lost person” searches each year. The frequency of “lost person” searches conducted by First Responders (Law Enforcement, Fire/Rescue, Search and Rescue) is increasing but changing from primarily lost children (including those with autism) to people who are despondent, aged adults with various forms of dementia, and people out for day hikes, among many other types.


The types of actions taken in the first minutes and hours of a search can make the difference as to whether these actions result in successfully finding the person alive and well or not. While a lot of training has been developed and conducted for First Responders, what is needed is additional research on the various categories of “lost people,” (such as hikers, people with dementia, children, hunters, among others), identifying the key attributes derived from past experiences which can lead to them being “found” quicker, and the development of easy to follow instructions which can be used by the “first on scene” resources to get started.
 

Typically, the urban search involves either a lost child, or an elderly person suffering from some form of dementia. It is often similar for the rural and wilderness search. Much of the critical information must be gathered from the family and friends through the interview and investigative process. This all takes time while the lost person may be traveling farther away from the initial area. Time is the critical element in this process and an organized course of action for identifying the critical information and then obtaining it is necessary.
 

Search and Rescue theory and the suggested deployment of tactical resources are based upon the Probability of Success Rate (PSR). The major components of determining the PSR is the speed of Search and Rescue (SAR) resources, the Probability of Detection (POD), and the Probability of Area (POA). First responders responding to lost persons incidents are required to file reports but quick access to these reports are rarely possible during real time incident response. Determining the POD in the land environment has also been problematic. Products or procedures that can capitalize on existing GIS information such as Light Detection And Ranging (LIDAR) data to provide a predictive sweep width value (a component of determining POD) may prove valuable. A database of environmental and terrain conditions that might predict the sweep width value is another approach. Although many databases exist, there is no tool that is able to quickly search and analyze the stored information to arrive at the best possible approach to finding the lost person. 

Keywords: Survivability, Search and Rescue, lost person searches, search planning and management, SAR theory, wandering, Alzheimer patient.
H-SB013.2-004: Structural Collapse Prediction Technology
Description:

Numerous first responders have been killed in the line of duty as a result of structural collapse, from the 343 firefighters who lost their lives in the September 11, 2001 World Trade Center collapse to the firefighters and other first responders, and civilians who are killed or injured performing their regular duties from collapsing structures, including incidents involving single family dwellings.


There is a need for accurate and easily deployable technology to predict structural collapse to avoid or reduce these incidents. The development of a small vibration sensing technology including development of hardware with wireless solid-state electronic sensors and base display units, as well as the interpretation algorithm necessary to translate the vibration data from the sensor into a “green/yellow/red” tactical decision aid to alert incident commanders of a pending collapse is a high priority technology.


The Department of Homeland Security (DHS) Federal Emergency Management Agency (FEMA), the United States Fire Administration (USFA), and the National Institute of Standards and Technology (NIST) have been investigating the use of new measurement technologies in the fire environment for the prediction of structural collapse. This includes the use of thermal imaging technology to measure temperature, lasers to measure building displacement, and vibration sensors to measure changes in the frequency of the building structure during the fire. Full-scale fire experiments have been conducted on a number of structures, including “traditional wood frame,” engineered wood truss, and lightweight steel truss construction. The results of these experiments indicate that the vibration-sensing technique has the best potential for reliable prediction of structural collapse. As a result, this project is focused on this technology. While vibration sensing technology has the best potential for reliable prediction of structural collapse, devices used in initial collapse prediction experiments are very large, cumbersome, and rudimentary. Therefore, there is a need to support the development of a smaller advanced prototype. 

Keywords: First responders, early warning system, danger detection, building collapse
H-SB013.2-005: Commodity Goods Counterfeit Detection
Description:

Counterfeiting is a serious problem impacting customers and producers in the global economy. There are two separate issues - the economic impacts from purchasing a counterfeit consumer retail product, and the health risks associated with a consumer purchasing and consuming a counterfeit pharmaceutical product. This effort focuses on the consumer retail products only, as the detection methods for the two problem spaces are very different.


Product counterfeiting is a form of consumer fraud: a counterfeit product is sold, purporting to be something that it is not. As a result, most product counterfeiting is considered to be criminal in nature under typical trade conventions. The key technical challenge to be considered is how to differentiate a possibly visibly identical counterfeit product from the authentic item. One of the key observables lending itself to automated-machine detection is testing for inferior-grade materials. 

Keywords: Consumer commercial counterfeit products, inferior-grade counterfeit materials, counterfeit seizures, counterfeit seizures by product type, comparison of counterfeit and authentic materials quality
H-SB013.2-006: Management of Mass Casualty Triage
Description:

Current mass casualty triage patient tracking techniques rely on paper forms, analog voice communications, and colored vinyl tape or tags. At best, these techniques may also include the use of radio-frequency identification (RFID) tags. Although all these techniques are robust, have a long shelf life, and do not require any type of external power source, they are not scalable for very large incidents such as may result from an urban area terrorist attack, hazmat spill, or natural disaster. In addition, the Emergency Services sector is comprised of many independent components that it is difficult to even know what technologies, if any, are being utilized. 

Keywords: emergency response, mass casualty incident, MCI, triage, patient care reports, barcode ID, digital/RFID
H-SB013.2-007: Affordable Non-Destructive Anomaly Detection for Perceived Hollow Spaces
Description:

The Department of Homeland Security (DHS) has identified a need to detect narcotics, weapons, explosives or other contraband smuggled over the border, onto planes, or carried into public venues while concealed in hollow spaces such as bicycle, stroller, or wheelchair frames. Agents and officers require reliable and easy-to-use tools that can quickly provide a general primary screening of these items to determine if a usually perceived hollow space is empty or dense. This primary screening device will determine if a secondary examination for a more in-depth inspection is required. 

Keywords: explosives detection, narcotics detection, drug detection, smuggling, empty volume detection, wheel chair screening, bicycle screening, stroller screening
H-SB013.2-008: Pre-Shot Sniper Detection in Urban Environments
Description:

Currently there is no product that can reliably detect and locate, in all weather conditions that a sniper would operate in, a sniper amongst the clutter of an urban environment before they fire their weapon. Although law enforcement can establish security perimeters and control items entering the space, they are also concerned about threats from outside the security perimeters. These threats include snipers outside the security perimeter. “Pre-shot” allows for security force response to dissuade/prevent an adversary from getting the shot off in the first place.


There are several factors challenging today’s detection technologies that need to be addressed, including the following three challenges. First, law enforcement needs the ability to locate a sniper amongst objects and people surrounding them at all times of the day, and in all weather conditions. Objects commonly found in an urban environment such as traffic lights, signage, vehicles and building features can be distracting to the detection system and create clutter. People carry objects and devices that create clutter. Second, a sniper must be detected from a different location than the protection area. Detectors need to cover a wide area. Finally, the technology must be portable. The need to detect snipers moves from one location to another. Law enforcement needs to set up the technology and make it operational within hours of events and activities, and then the technology needs to be dismantled and moved somewhere else for another event.
 

The proposed solution must be able to detect and locate amidst the noise of an urban environment and in all weather conditions sniper behavior, actions, or weapons before a weapon is fired. The proposed solution must be able to detect and locate a weapon trained on a target from outside the weapon’s line-of-fire (off-axis). Wide area coverage is highly desirable. The proposed technology must be sized to be moved and set up by one person and moved with a “two man lift” limit of 75 pounds for heavier components. 

Keywords: sniper detection, Pre shot, sniper, optical sniper, radar sniper