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Deep learning detects lithium batteries in luggage and cargo

Deep learning detects lithium batteries in luggage and cargo

New Products |
By Nick Flaherty



The HI-SCAN 100100V-2is and 100100T-2is scanners are the first to add a series of smart and adaptable algorithms for the automatic detection of an ever expanding list of dangerous, prohibited and contraband goods and substances. Other conventional X-ray systems can also be upgraded, and existing installations can be upgraded on site

The company is working with customers to build a library of images from which the algorithms can ‘learn’ to detect many other items. “The lithium battery development follows IATA’s recommendations regarding Dangerous Goods and is aimed mainly at the air cargo sector,” said Matt Clark, VP Technology & Product Development at Smiths Detection. “It is designed to tackle the tangible threat posed by lithium batteries, which have the potential to ignite when airborne. In addition to extending this option to a full range of systems, we plan to expand these augmented detection capabilities to goods such as weapons, flammable liquids, currency and drugs.”

The HI-SCAN 100100 series was first in line for the lithium battery option for freight and cargo operators. Positioned at 90° to each other, two 160 kV generators speed up the inspection time of tightly packed items by providing both horizontal and vertical views. For further efficiency, there is a choice of conveyor heights and a maximum load of 220kg. HI-SCAN 100100 series scanners are compliant with EU regulation 2015/1998.

The lithium battery kit uses an external evaluation computer to host the detection software, which analyses the contents and “frames” any detected batteries – this data can be shown on the main system monitor or on an additional screen. Adding this detection function does not affect the speed of overall image evaluation and little or no training is required. It is available now as an option on new HI-SCAN 100100 series scanners or as an upgrade for existing machines.

www.smithsdetection.com

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