Researchers at Texas A&M University’s College of Engineering have developed Smart-Sea, a real-time collision avoidance system designed to reduce marine collisions and allisions by combining radar data, vessel maneuverability, and seafarer experience. Using raw radar imagery processed through machine learning, the system identifies and classifies nearby stationary objects such as offshore platforms and wellheads, then recommends safe maneuvering actions based on vessel performance characteristics and the operator’s experience level. Smart-Sea delivers guidance visually or audibly without taking control of the vessel, keeping decision-making in the hands of the seafarer. Developed in collaboration with former mariners, industry experts, the U.S. Navy, and the U.S. Coast Guard, the system has been tested aboard Texas A&M’s research vessel Trident, with early results indicating it could significantly reduce collision risks in all weather conditions. Researchers say the low-cost design could eventually make the technology viable not only for commercial shipping but also for recreational vessels, improving safety across the maritime sector.