Machine intelligence could make it easier to spot illicit cargo among the goods that move through the world's ports.
Pacific Northwest National Laboratory's Antonio Sanfilippo has led the development of a data-mining system that is designed to scan millions of ship manifests to find questionable cargoes. His team developed an algorithm to analyze 2.4 million shipping records from industrial data broker PIERS. The algorithm uses the manifest information to assign a record to one of 25 clusters, and then finds the outlying records in each cluster, which are those that do not fit in with the existing patterns for those routes, or are carrying an unusual cargo for that ship. Suspicious records would then be investigated.
Sanfilippo plans to use the data to create a network of all the shipping organizations and their connections in order to enable the system to spot suspicious links.
The Stockholm International Peace Research Institute's Hugh Griffiths notes preventing smuggling is getting increasingly complex. "It's become much harder to detect narcotics shipments, counterfeit goods, and arms," Griffiths says. "It's a very complex issue, and no one has been able to solve it."
From New Scientist
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