AI predicts whale movements to reduce deadly ship strikes

An artificial intelligence (AI) tool has been developed to predict the habitat of endangered whales, helping to reduce deadly ship strikes and promote responsible ocean development. The tool was designed by researchers at Rutgers University-New Brunswick.

By analyzing vast datasets, the AI model improves existing monitoring techniques, offering a more precise way to track the movements of the critically endangered North Atlantic right whale.

This species has been listed as endangered under the Endangered Species Act since 1970. Currently, the whales have an estimated population of only 370 individuals, including around 70 reproductively active females, according to the U.S. National Oceanic and Atmospheric Administration (NOAA).

Mapping whale movements with AI

The project was led by Ahmed Aziz Ezzat, an assistant professor in the Department of Industrial and Systems Engineering at Rutgers’ School of Engineering. 

Ezzat collaborated with Josh Kohut, a Rutgers professor of marine sciences, and doctoral student Jiaxiang Ji, who is the study’s first author.

Professor Kohut likened the AI model’s function to tracking human movement patterns in a household, where factors like food in the kitchen or a television in the den influence where people gather at specific times.

“With this program, we’re correlating the position of a whale in the ocean with environmental conditions,” Kohut explained. “This allows us to become much more informed on decision making about where the whales might be.”

“We can predict the time and location that represents a higher probability for whales to be around. This will enable us to implement different mitigation strategies to protect them.”

Valuable tools for the blue economy

The researchers initially aimed to create high-resolution habitat models to support offshore wind farm development. However, their findings have broader implications, prompting them to publicly share additional details as part of their study.

“These tools are valuable and would solidly benefit anyone engaged in the blue economy – including fishing, shipping and developing alternative forms of energy sustainably,” said Ezzat. 

“This approach can support a wise and environmentally responsible use of these waters so that we achieve our economic objectives, and at the same time make sure that we cause minimal to no harm to the environmental habitat of these creatures.”

How AI enhances whale tracking

Unlike traditional programs that operate on fixed instructions, the machine-learning model used in this study analyzed massive datasets to detect patterns and refine its predictions over time.

“The outcome of the machine-learning model is basically a prediction of where and when you will have a higher likelihood of encountering a marine mammal,” Ezzat said, describing it as a “probability map.”

The model integrated data from the Rutgers University Center for Ocean Observing Leadership, which has been gathering whale detection and oceanographic data since 1992. The analysis also incorporated satellite data from the University of Delaware.

Leveraging ocean data for conservation

To build an accurate predictive tool, the researchers used two primary sources of oceanographic data: autonomous underwater gliders and satellite-based measurements.

Underwater gliders, torpedo-shaped robotic vessels, collect real-time information on seawater temperature, salinity, currents, and chlorophyll levels. They also use sonar to assess fish populations and record whale vocalizations, allowing researchers to pinpoint their locations.

Meanwhile, satellite data provides broader environmental context, including sea surface temperature, water color, and oceanic fronts—factors that influence whale distribution.

“We’ve had the data but, until now, we’ve not been able to put the two sets – those detections of where the whales are, and what the environment is like at those places – together,” Kohut said. “This is a demonstration of the power of employing AI methodologies to advance our ability to predict or estimate where these whales are.”

Protecting whales with AI

By harnessing AI to integrate decades of environmental and whale tracking data, the Rutgers team has developed a powerful tool to improve conservation efforts, mitigate ship collisions, and support sustainable ocean development. 

As human activities increasingly intersect with marine ecosystems, this AI-driven approach provides a critical step toward protecting North Atlantic right whales and ensuring responsible management of ocean resources.

The study was published in the journal Nature Scientific Reports.

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