Researchers have used artificial intelligence to help authorities more easily decipher what vessels might be doing when they go dark—and whether they might be fishing illegally.
slipped into Argentinian waters and deployed its trawl nets, hauling in more than 140 tons of hake, skate, and squid. The ship did not have permission to fish those waters, according to Argentine officials, and to avoid detection the crew turned off a beacon that sends a vessel’s precise location via satellite to maritime authorities.
To researchers, the records of these locations yield telltale signs of activity: Vessels will travel in one direction to lay out a drifting long line of baited hooks, then double back to haul in the catch. Ships pursuing tuna make looping patterns as they encircle a school of fish with a giant net.
First, the researchers identified case studies that clearly looked like deliberate beacon deactivation, for example where the signal abruptly ceased and later turned on again at full strength. They also found examples where the problem seemed to be technical, such as a weakening and intermittent signal. These examples helped train the machine learning programs to recognize signs of ships trying to evade detection.
Pramŏd Ganapathiraju, a consultant in fisheries enforcement, calls the research “an excellent piece of work,” because the analysis shows which country’s fleets are most likely to turn off their AIS beacons. Cases near an Exclusive Economic Zone frequently involved Chinese- and Spanish-flagged ships. Details of locations, times, and vessels will help coastal states take action against the suspected illegal activities, says Ganapathiraju, who was not involved in the research.
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