Researchers in Australia have developed an AI system to detect smuggled marine wildlife products, including shark fins, dried seahorses and sea cucumbers, in airport luggage scans.

The study uses existing 3D X-ray CT airport scanners and a neural network to identify trafficked items concealed in baggage with 92 per cent accuracy, according to a statement from the journal Frontiers in Ocean Sustainability on Monday.

Marine wildlife trafficking, estimated to generate billions of dollars annually, poses a major threat to ocean ecosystems.

Unlike more widely recognised wildlife crimes, such as ivory or rhino horn trafficking, illicit trade in marine species is harder to detect as items are often hidden in ordinary travellers’ luggage or packages, the statement said.

To train the algorithm, the team led by scientists at Australia’s Macquarie University conducted nearly 300 scans using samples of marine wildlife trafficking seizures.

The scans simulate smugglers’ tricks and real-life circumstances such as wrapping items in tin or clothes, or hiding them inside toys.

The system achieved detection rates of 95 per cent for shark fins, 96 per cent for seahorses, and 86 per cent for sea cucumbers, researchers said.

They said the technology could support border enforcement efforts but emphasised that it would complement, not replace, existing detection methods, noting limitations such as false positives and uneven access to advanced 3D scanners.

“AI is not a silver bullet for detection, nor a replacement for human and sniffer dog detection,” said Vanessa Pirotta of Macquarie University, the study’s lead author. 

(Xinhua/NAN)