Research on Intelligent Ship Supervision System Based on Lambda Architecture

With the increasing prosperity of the shipping industry, the vessel monitoring system has become increasingly important for improving the safety and operational efficiency of vessels. AIS (Automatic Identification System) provides real-time and accurate information for vessel monitoring by exchanging information such as vessel position, sailing speed, and heading. To achieve real-time vessel monitoring and deep mining of navigation data, an intelligent vessel monitoring system based on AIS data is designed and implemented. The system implements data processing based on the Lambda architecture, realizes offline analysis of navigation data through Spark + Hive, and realizes real-time processing of navigation data through Flink, which simultaneously satisfies the needs of offline and real-time data processing. The system builds a multi-level storage architecture based on technologies such as Redis, MySQL, HBase, and Hive, achieving different data storage and query requirements. The system realizes data visualization based on the front-end and backend separation technology, builds back-end interfaces through Spring Boot, and builds a visualization interface through technologies such as Vue, Echarts, and Mapbox. The intelligent vessel monitoring system can provide accurate vessel locations and navigation statuses in a timely manner, which helps prevent potential risks of vessels, promotes the advancement of vessel monitoring technology, and facilitates the sustainable development of the shipping industry.