MIT search-and-rescue algorithm helps find missing objects and people

The ocean is vast, and it can be difficult to find missing objects and people in it. To help search and rescue missions, MIT has developed a new algorithm that helps to identify hidden “traps” in ocean waters. Researchers say that the method could help quickly identify regions where objects and missing people may have converged.

Scientists at MIT worked with researchers from the Swiss Federal Institute of Technology, the Woods Hole Oceanographic Institution, and Virginia Tech to develop the new technique. Researchers hope that the technique will help first responders quickly zero in on regions of the sea were missing objects, or people are likely to be. The algorithm analyzes ocean conditions such as the strength and direction of ocean currents, surface winds, and waves to identify in real-time the most attracting regions of the ocean where floating objects are likely to converge.

The team demonstrated the technique in several field experiments where they deployed drifters and human-shaped manikins in various locations of the ocean. They found over a few hours, the objects migrated to regions that the algorithm predicted would be strongly attracting based on present ocean conditions. The algorithm can be applied to existing models of ocean conditions in a way that allows rescue teams to quickly uncover hidden “traps” where the ocean may be steering missing people at any given time.

The new tool can be run on various models to locate these traps where search and rescue teams could find a missing person or stranded vessel. The method the team developed to interpret the complex flow of the ocean uses advanced, data-driven ocean modeling and prediction systems. The model uses a “Eulerian” approach rather than the most commonly used “Langrangian” approach.

Those mathematical techniques that involve integrating snapshots of the ocean velocity due to the waves and currents to slowly generate a trajectory for where missing person or object may have been carried. The approach has been called TRAPS, standing for Transient Attracting Profiles.

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