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Coke-snorting cop bots to replace sniffer dogs

Roboplod finds could count as evidence in court

The smart choice: opportunity from uncertainty

Sniffer dogs can get tired, but fibre-optic sniffer robots don't have the same problem. And they are just as good at detecting cocaine, says Tong Sun, a professor of sensor engineering at City University London.

Prof Sun and her team won a £140k grant on Tuesday to work on the coke-detecting robots that they foresee will reduce the number of sniffer dogs needed in places like airports. This is on top of a previous award of £550,000 for both the drug-detecting sensor project and project working on a sensor that can smell your fear... Sun won previous funding for work on sensors that detect the alarm pheromones released by humans when they are scared.

"Sniffer dogs are used in such situations, but they have a high cost of upkeep, can get tired and confused, and cannot act as evidence in court," said the grant-awarding body the Engineering and Physical Sciences Research Council (EPSRC), which is funding the university team's collaboration with the Home Office Scientific Development Branch and sensor-maker Smiths Detection.

Other sensor tech currently on the market cannot match the dogs:

The limitations of existing technologies include high levels of false alarms, low levels of sensitivity compared to sniffer dogs and high cost using disposable consumables.

The City team's breakthrough was to use the molecularly imprinting polymer (MIP) technique coupled with fluorescence signalling. The result is a portable, fibre-optic sensor that is sensitive but selective, producing fewer false alarms. The purpose of the new grant is to bring the sniffer tech to market. Professor Sun's team plan to have a prototype within a year that can be used for checking hard-to-reach places like shipping containers and cars.

The Register's own efforts at robotic animals have not yet attracted this level of public funding, though our in-house robotic sheep is capable of both moving and cutting grass. ®

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