AI Wildlife Detection Tool Catches Smuggled Marine Species Hidden in Airport Luggage

Can AI detect smuggled sea cucumbers?

I agree my information will be processed in accordance with the Scientific American and Springer Nature Limited Privacy Policy. We leverage third party services to both verify and deliver email. By providing your email address, you also consent to having the email address shared with third parties for those purposes. Scientists hoping to stop the illicit trade of marine wildlife have a new tool to spot seahorses, shark fins and sea cucumbers hidden in luggage. The tool, which uses artificial intelligence, could be deployed at airports to bolster wildlife enforcement efforts, the researchers say. Wildlife trafficking is a major industry: around the world, some $20 billion in plant and animal products are sold illegally every year, according to the International Criminal Police Organization (INTERPOL). That includes marine species -- such as sea cucumbers, seahorses and shark fins, which are illegally harvested and sold for possible medicinal uses or as food. Many of these wildlife products pass through airports and often go undetected, environmental advocates say. In the new study, which was published on Sunday in the journal Frontiers in Ocean Sustainability, researchers trained an AI algorithm on hundreds of three-dimensional x-ray images -- the kind of imaging already used in airports -- of 68 dried shark fin, seahorse and sea cucumber samples. Across hundreds of images, the algorithm correctly identified these samples 92 percent of the time, with a false positive rate of about 13 percent. On supporting science journalism If you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today. "Never in my career would I think AI would be such an important part of my research," says Vanessa Pirotta, lead author of the study and a wildlife scientist at Macquarie University in Australia. X-ray imaging "enables us to look in and around luggage and mail items -- this means we can use this tech to understand how people may change their trafficking efforts over time," she says. The algorithm, she adds, is aimed at "building our detection capacity" and is not intended to replace "manual human inspection" or "biosecurity dogs." From here, Pirotta hopes to deploy a version of this technology in airports. "The next step is working toward making these algorithms active at front lines around the world -- this is likely to help fill those gaps regarding occurrence and support enforcement efforts," she says.

Seahorses and shark fins are illegally trafficked. An AI tool could help stop this crime

Shark fins on a plane, seahorses in your bag and sea cucumbers in the post - these are just a few examples of illegal marine wildlife trafficking. This crime can be hard to detect. But in a new study, published in the journal Frontiers in Ocean Sustainability, we show how artificial intelligence (AI) can be harnessed as a complimentary detection tool to help stop marine wildlife trafficking at international airports and mail facilities. A global crime The cross-border trade in live animals, animal parts or products is a global crime, facilitating the flow of billions of illicit dollars each year. It's known to converge with other criminal activity, including the trafficking in drugs, arms and humans. The United Nations Office on Drugs and Crime identifies five sources of demand for wildlife trafficking: food, medicine, pets and ornamental plants, specialist collection and adornment. In some cases, such as pet prestige, people are motivated both by the desire to have a pet and the perceived status it brings to own an exotic animal. People traffic marine animals too Wildlife trafficking affects around 4,000 species. Many of the more well-known examples involve land-based animals - ivory from elephant tusks, horns from rhinos and scales from pangolins - the world's most trafficked mammal. Closer to home, we also see native Australian reptiles and birds, sometimes shoved in tins, put in socks and packaged up live to be sent overseas. Marine creatures, unfortunately, are targeted too. This can include live animals such as fish in people's bags, or dried marine life such as the rise of the seahorse trade and demand for shark fin. We have small pockets of knowledge of this activity. But the reality is we don't fully understand how widespread it is. AI to detect marine wildlife trade Currently, the best means of detecting illegally trafficked wildlife is humans. And then there are our four-legged friends: biosecurity dogs. Recently, Australia has also been working to develop the use of AI as a potential means of detecting land-based wildlife in illegal wildlife movements - building on existing detection pathways using 3D X-ray machines fitted with algorithms. For our latest study, we built on these efforts by developing world-first marine wildlife algorithms. We taught computers to look for shark fins, seahorses and sea cucumbers. We did this by collecting a total of 68 samples of dead marine animals, which we scanned in a 3D X-ray machine to create a library of images. We then used this image library to develop algorithms to enable computers to search for what we taught it to look for - in this case, shark fins, seahorses and sea cucumbers. Samples were scanned alone and then in more complicated scenarios to reflect how people actually traffic marine life. This means if a bag or mail item is hiding a shark fin, seahorse or sea cucumber, the algorithm will be able to flag this to an operator, prompting them to inspect the item. Out of a total of 298 scans and a training data set derived from these samples, our algorithm had success rates of 95%, 95% and 85% for shark fins, seahorses and sea cucumbers, respectively. Humans and biosecurity dogs still needed alongside AI While technology fitted with computer algorithms may help people inspecting luggage or mail, we still need people to verify what computers see. Sometimes the algorithms get it wrong and may miss items. Despite this, the broader implications of having AI as a second set of eyes searching for trafficked marine life will aid in identifying key trade routes to potentially stop this activity. The next step is relying on implementation of these algorithms at the front lines. Like computer algorithms and AI, the more we learn, the better we get at detecting and potentially stopping this harmful crime.

AI helps airports spot smuggled wildlife hidden in luggage

Wildlife trafficking is often associated with ivory, rhino horns, and exotic pets. Far less attention goes to the illegal trade in marine species, even though it threatens some of the ocean's most vulnerable animals. Shark fins, seahorses, and sea cucumbers are smuggled across international borders every year. Often dried and concealed inside ordinary luggage or parcels, they can be difficult for authorities to detect. A team of scientists in Australia decided to fight back. They taught a computer to spot these hidden animals on its own. Wildlife trafficking of marine animals The illegal wildlife trade is worth billions of dollars a year, which makes it one of the most profitable crimes on the planet. Sea creatures are part of that trade, but they rarely get noticed. "The trade of wildlife is cruel and unethical," said Dr. Vanessa Pirotta of Macquarie University, who led the study. Smuggled marine animals threaten fragile populations that are already under pressure. Some are sold for food, others for medicine or as ornaments, and a few are shipped alive and can turn invasive if they escape. "For many, this may be the first people have heard of illegal trafficking of marine wildlife," Pirotta said. She added that the trade reaches far beyond familiar targets like rhino horn and elephant ivory, and that World Oceans Day was a chance to bring the issue to the surface. The hard part is catching it. If officers cannot find the smuggled goods, they cannot stop the trade or even measure how much damage it does. Three creatures, one problem The team focused on three animals that smugglers move often. Each one tells a different part of the story. Shark fins are in high demand for food and make up the largest known share of the marine trade. Dried seahorses are sold for traditional medicine and turn up in dozens of countries. Sea cucumbers are the third member of the group. People know they are overfished, and the researchers suspect they are smuggled far more than the records show. Scanners borrowed from airports Instead of building something from scratch, the scientists used a machine that already exists. The Rapiscan Real Time Tomography 110 sits in airports and mail centers, where it normally checks bags for explosives. This scanner takes many X-rays of a single object and stitches them into a full 3D picture. An operator can spin the image around and study a hidden item from any angle. That extra dimension matters. A dried seahorse wrapped inside a sock looks very different from the side than from the top. Teaching a computer to see The researchers fed these 3D scans into a type of artificial intelligence (AI) that learns shapes the way we learn faces. The more examples it sees, the better it gets. They scanned 68 real samples, including 18 shark fins, 30 seahorses, and 20 sea cucumbers, many taken from actual trafficking seizures. Each sample was scanned five times in different positions, and the team even copied smugglers' tricks by hiding items in clothing, tin, and children's toys. Real samples were scarce, so they used a clever shortcut. Software dropped scanned animals into pictures of normal, harmless bags, which gave the computer thousands of realistic examples to practice on. The numbers look promising Then came the real test. The team showed the system bags it had never seen before and watched how it performed. The results were strong. The AI system caught shark fins 95% of the time, seahorses 96% of the time, and sea cucumbers 86% of the time, for an overall success rate of 92 percent. False alarms stayed low too, at 13% across the board. The researchers believe these are the first detection tools built specifically for trafficked marine life. Where the system falls short Some animals are too small or too light to show up clearly on a scan, so the machine can still miss them. "We can only mock up real-world trafficking scenarios based on what has been detected before," Pirotta said. The study also relied on a small pool of real samples. That means the tool may behave differently once it faces the messy variety of a real border. A helper, not a hero This software is meant to work alongside people, not take their place. Even a low false alarm rate means an officer still has to open flagged bags and check by hand. "AI is not a silver bullet for detection, nor a replacement for human and sniffer dog detection," Pirotta said. Detection dogs and manual searches still matter. There is also the cost, since these 3D scanners are expensive and many airports still rely on older 2D machines that cannot run the new program. Future of marine trafficking control Even with those limits, the promise is real. As airports and mail hubs upgrade their scanners, the same machines that hunt for explosives could double as guardians of the sea. The researchers hope wider sampling will make future versions even sharper. A scanner that never gets tired might give threatened ocean life a real chance at the border. The study is published in the journal Frontiers in Ocean Sustainability. -- - Like what you read? Subscribe to our newsletter for engaging articles, exclusive content, and the latest updates. Check us out on EarthSnap, a free app brought to you by Eric Ralls and Earth.com.