{"id":22871,"date":"2026-01-06T19:02:35","date_gmt":"2026-01-06T19:02:35","guid":{"rendered":"https:\/\/krogragg.com\/?p=22871"},"modified":"2026-01-06T19:02:35","modified_gmt":"2026-01-06T19:02:35","slug":"texas-am-develops-ai-powered-smart-sea-system-to-help-seafarers-avoid-collisions","status":"publish","type":"post","link":"https:\/\/krogragg.com\/?p=22871","title":{"rendered":"Texas A&M Develops AI-Powered SMART-SEA System To Help Seafarers Avoid Collisions"},"content":{"rendered":"\n
Texas A&M Develops AI-Powered SMART-SEA System To Help Seafarers Avoid Collisions<\/div>\n

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Collisions between marine vessels and stationary structures, like offshore oil platforms and depleted wellheads, are becoming increasingly common. These collisions come with a cost \u2014 including the financial burden of lost goods and potential loss of life.<\/p>\n

Ocean engineering researchers at Texas A&M University are developing a smarter system to combat these collisions and their costs. By combining raw radar imaging data with advanced machine learning, researchers have created SMART-SEA, a system that gives seafarers real-time guidance on how and when to maneuver their vessel.<\/p>\n

To design a practical system for seafarers, researchers conducted a focus group with Texas A&M at Galveston faculty members, many of whom are former seafarers.<\/p>\n

Researchers also collaborated with industry experts, the U.S. Navy and the U.S. Coast Guard. Their experience assisted researchers in defining practical decision-making skills \u2014 like when to yield and how far to turn \u2014 and implementing them into the SMART-SEA system.<\/p>\n

\u201cMany of these collisions are caused by human error,\u201d said Dr. Mirjam F\u00fcrth, an assistant professor of ocean engineering. \u201cBy using data to provide seafarers with real-time instructions, we hope to reduce marine collisions.\u201d<\/p>\n

At its core, the SMART-SEA system aims to provide seafarers with the ideal maneuvers to ensure vessel safety, without controlling movements autonomously. SMART-SEA provides the information visually on a dashboard, but the decision and steering of the vessel is controlled by the seafarer.<\/p>\n

Key data points used by SMART-SEA to provide maneuvering suggestions are raw radar images and vessel maneuverability \u2014 determined through a tiered model based on seafarer experience, state of the art computational fluid dynamics models and machine learning trained on past vessel motions.<\/p>\n

Raw radar images are processed using a machine learning tool that identifies and classifies stationary objects near the vessel. Once identified, the vessel\u2019s maneuverability and seafarer\u2019s experience level are considered to recommend the safest action for the vessel.<\/p>\n

F\u00fcrth and her team, including former seafarer and Texas A&M Galveston Professor of Practice Ryan Vechan, tested SMART-SEA aboard the Texas A&M research vessel Trident, with preliminary data supporting the prototype as a way to reduce marine collisions.<\/p>\n

SMART-SEA can detect stationary objects in all weather conditions, and seafarers can choose how to receive the data \u2014 either visually, audibly or a combination of the two.<\/p>\n

\u201cI do think SMART-SEA could reduce marine collisions and possibly pave the way for more autonomous vessels,\u201d F\u00fcrth said.<\/p>\n

The project\u2019s initial funding came from the U.S. Department of the Interiors and the U.S. Department of Energy through the Ocean Energy Safety Institute under a one-year contract.<\/p>\n

Researchers hope to secure additional funding to continue testing SMART-SEA on other vessels and to improve the system. F\u00fcrth believes that the system\u2019s low costs could allow it to be adapted for recreational vessels, reducing boating accidents.<\/p>\n

\u201cI hope we get to continue this research in the future. I think we just scratched the surface,\u201d said F\u00fcrth.<\/p>\n

Also collaborating on this research from the ocean engineering department are Ph.D. students Andrew Deng and Yijun Sun, Research Assistant Professor Dr. Bj\u00f6rn Winden, and Assistant Professor Dr. Freddie Witherden.<\/p>\n

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Texas A&M Develops AI-Powered SMART-SEA System To Help Seafarers Avoid Collisions Image for representation purposes only Collisions between marine vessels and stationary structures, like offshore oil platforms and depleted wellheads, are becoming increasingly common. These collisions come with a cost \u2014 including the financial burden of lost goods and potential loss of life. Ocean engineering […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[194,196],"tags":[197],"class_list":["post-22871","post","type-post","status-publish","format-standard","hentry","category-marine-insight","category-shipping-news","tag-marine-insight"],"_links":{"self":[{"href":"https:\/\/krogragg.com\/index.php?rest_route=\/wp\/v2\/posts\/22871"}],"collection":[{"href":"https:\/\/krogragg.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/krogragg.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/krogragg.com\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/krogragg.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=22871"}],"version-history":[{"count":0,"href":"https:\/\/krogragg.com\/index.php?rest_route=\/wp\/v2\/posts\/22871\/revisions"}],"wp:attachment":[{"href":"https:\/\/krogragg.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=22871"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/krogragg.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=22871"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/krogragg.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=22871"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}