Algorithm speeds up ocean search-and-rescue missions

A new algorithm can speed up search and rescue operations at sea, according to a new study.

The algorithm accurately predicts locations to which objects and people floating in water will drift.

Hundreds of people die at sea every year due to vessel and airplane accidents. Emergency teams have little time to rescue those in the water because the probability of finding a person alive plummets after six hours. Beyond tides and challenging weather conditions, unsteady coastal currents often make search and rescue operations exceedingly difficult.

New insight into coastal flows promises to enhance the search and rescue techniques currently in use.

“Our work has a clear potential to save lives,” says Mattia Serra, former PhD student at ETH Zurich who is now a postdoctoral fellow at Harvard University and first author of the study in Nature Communications.

In today’s rescue operations at sea, elaborate models of ocean dynamics and weather forecasting are used to predict the path of drifting objects. For fast-changing coastal waters, however, such predictions are often inaccurate due to uncertain parameters and missing data. As a result, a search may be launched in the wrong location, causing a loss of precious time.

Haller’s research team obtained mathematical results predicting that objects floating on the ocean’s surface should congregate along a few special curves which they call TRansient Attracting Profiles (TRAPs).

These curves are invisible to the naked eye but the researchers’ mathematical methods can extract and track them from instantaneous ocean surface current data. This enables quick and precise planning of search paths that are less sensitive to uncertainties in the time and place of the accident.

The researchers tested their new, TRAP-based search algorithm in two separate ocean experiments near Martha’s Vineyard near the northeastern coast of the United States. Working from the same real-time data available to the Coast Guard, the team successfully identified TRAPs in the region in real time. They found that buoys and manikins thrown in the water indeed quickly gathered along these evolving curves.

“Of several competing approaches tested in this project, this was the only algorithm that consistently worked in situ,” says George Haller, professor of nonlinear dynamics.

“Our results are rapidly obtained, easy to interpret, and cheap to implement,” Serra says.

He adds that the method they have developed also has the potential to predict the evolution of oil spills. The researchers next plan to test their new prediction tool in other ocean regions.

As Haller stresses: “Our hope is that this method will become a standard part of the toolkit of coast guards everywhere.”

Additional researchers from MIT contributed to the work.

Source: ETH Zurich

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