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Robotic Ferret Will Detect Hidden Drugs, Weapons and Humans in Containers


Robotic Ferret
Robotic Ferret

June 12, 2009 By

The U.S. maritime system consists of more than 300 sea and river ports with more than 3,700 cargo and passenger terminals. Its ports handle approximately 20 percent of all the maritime trade worldwide and it is this volume of trade that makes ports a key target for potential terrorist attacks.

Cargo containers in particular represent the largest area of concern in terms of security and vulnerability. With an estimated 12 million containers in current circulation worldwide, the task of securing, tracking and inspection all of these is difficult.

A large container ship has the capacity to carry in excess of 3,000 containers, making inspection impossible without disrupting shipment. More than 6 million cargo containers enter U.S. seaports annually, of which only a very small percent are physically inspected by Customs.

On top of any terrorist threat, drugs and even illegal immigrants are also smuggled in containers. However, help to increase port security may soon be at hand. A new type of robot being developed will make it easier to detect drugs, weapons, explosives and illegal immigrants concealed in cargo containers.

Dubbed the "cargo-screening ferret" and designed for use at seaports and airports, the device is being worked on at the University of Sheffield with funding from the Engineering and Physical Sciences Research Council (EPSRC). The idea for the project emerged from an event organized by EPSRC, the British Home Office Scientific Development Branch and the UK Borders Agency.

The ferret will be the world's first cargo-screening device able to pinpoint all kinds of illicit substances and the first designed to operate inside standard freight containers, according to a news release issued today.

It will be equipped with a suite of sensors that are more comprehensive and sensitive than any currently employed in conventional cargo scanners.

Recent advances in both laser and fiber-optic technology now make it possible to detect tiny particles of different substances. The EPSRC-funded project team is developing sensors which incorporate these technologies and that are small enough to be carried on the 30 cm-long robot, in order to detect the specific "fingerprint" of illegal substances at much lower concentrations than is now possible.

When placed inside a steel freight container, the ferret will attach itself magnetically to the top, then automatically move around and seek out contraband, sending a steady stream of information back to its controller.

Current cargo-screening methods rely on a variety of separate methods, such as the use of sniffer dogs and external scanners for detecting explosives and drugs, and carbon dioxide probes and heartbeat monitors to detect a human presence.

Cargo scanners currently in use at seaports and airports only generate information on the shape and density of objects or substances. The ferret, however, will be able to provide information on what they actually consist of as well.

The ferret will offer major advantages in combating human trafficking. Currently it is very difficult to detect people hidden in freight containers (e.g., the use of X-rays is prohibited due to the harm the radiation could do to anyone concealed there). Sensors on board the ferret will be able to detect tiny traces of carbon dioxide which indicate the presence of humans concealed in the containers.

Another key benefit is that the ferret will reduce the need for customs and security officials to enter or unpack freight containers, which is time-consuming and may expose officers to danger or possible contamination by harmful substances.

"It's essential we develop something which is simple to operate and which Border Agents can have total confidence in," said Dr. Tony Dodd, who is leading the project. "The ferret will be able to drop small probes down through the cargo and so pinpoint exactly where contraband is concealed."

Working prototypes of the cargo-screening ferret could be ready for testing within two years, with potential deployment within around five years.


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