Basic study on 3D undersea position estimation system using electromagnetic waves by machine learning

When divers are doing rescue operations in the sea, they are in a hazardous environment. If it becomes possible to know their positions accurately, rescue operations can be carried out more safely and reliably. We propose a subsea position estimation system using received signal strength (RSS) of electromagnetic waves to assist rescue operations by locating divers in the sea. In this report, as a basic study for introducing machine learning into the subsea position estimation system, four supervised machine learning models were used for undersea position estimation and each model is compared. The best model is Multi-Layer Perceptron (MLP), and it is confirmed that there is no problem in real-time computation time for all models.