Abstract
In the post September 11, 2001 (9/11) world the federal government has increased its focus on the
manufacturing, distributing, warehousing, and transporting of hazardous materials. In 2002, Congress
mandated that the Transportation Security Agency (TSA) designate a subset of hazardous materials that
could pose a threat to the American public when transported in sufficiently large quantities. This subset
of hazardous materials, which could be weaponized or subjected to a nefarious terrorist act, was
designated as Security Sensitive Hazardous Materials (SSHM). Radioactive materials (RAM) were of
special concern because actionable intelligence had revealed that Al Qaeda desired to develop a
homemade nuclear device or a dirty bomb to use against the United States (US) or its allies.1
Because of this clear and present danger, it is today a national priority to develop and deploy
technologies that will provide for visibility and real-time exception notification of SSHM and Radioactive
Materials “in Quantities of Concern” (RAMQC) in international commerce.
Over the past eight years Oak Ridge National Laboratory (ORNL) has been developing, implementing,
and deploying sensor-based technologies to enhance supply chain visibility. ORNL’s research into
creating a model for shipments, known as IntelligentFreight, has investigated sensors and sensor
integration methods at numerous testbeds throughout the national supply chain. As a result of our
research, ORNL believes that most of the information needed by supply chain partners to provide
shipment visibility and exceptions-based reporting already exists but is trapped in numerous proprietary
or agency-centric databases.
