Multi-level Ship Trajectory Query System Based on Flink

Abstract

Against the backdrop of increasingly frequent global maritime transportation and sustained growth in ship traffic, how to efficiently process and display vast amounts of ship trajectory data has become an important issue in smart maritime management. Traditional trajectory query systems mostly rely on batch processing, which is difficult to meet the multiple demands for real-time performance, visualization levels, and query efficiency. To address this challenge, this paper designs and implements a multi-level ship trajectory query system based on Flink, combining a stream computing framework with a front-end and back-end separation architecture to achieve real-time processing, hierarchical management, and dynamic visualization of ship trajectories. The system possesses strong practicality and promotional value. The back-end of the system uses Spring Boot to build core services, while the front-end uses HTML and JavaScript frameworks to implement interactive interfaces for users and administrators respectively. Apache Flink is introduced as a real-time data processing engine to perform high-throughput aggregation and thinning processing on AIS ship data. Trajectory data with different granularities are displayed according to different map zoom levels, thus ensuring trajectory integrity while optimizing query efficiency and front-end rendering performance.