Construction and Application of Intelligent Decision Aid System for Maritime Search and Rescue from the Perspective of Big Data

This paper proposes a design of intelligent decision aid system for maritime search and rescue based on big data. The system integrates the maritime search and rescue and evacuation model, uses the Lagrange tracking method to simulate the movement trajectory of the rescue ship and the target in distress, and introduces the random particle and drift dynamics model to cope with the complex and changeable sea conditions. In the system design, people pay special attention to the real-time and accuracy of data. Through big data technology, the system can collect, process, and analyze massive search and rescue data in real time, including meteorological information, ocean current data, ship location, etc., to provide comprehensive information support for decision makers. At the same time, the system also combines machine learning and artificial intelligence technology to deeply dig historical search and rescue cases and continuously optimize search and rescue strategies. In addition, the system has good scalability and compatibility, and can be seamlessly integrated with other maritime monitoring systems and emergency response platforms, forming an efficient and collaborative search and rescue network. The simulation results show that the system has excellent performance in improving search and rescue efficiency and reducing search and rescue risk, and has high practical value and popularization prospect.