A Study on Maritime Safety Risk Prediction of Unmanned Vessels from a Digital Health Perspective

Abstract

Improving the safety and reliability of unmanned vessels under the perspective of digital health is the key to ensure the safety of human and the health of natural ecology. This paper firstly designs the marine ecology navigation system through marine ecology and elaborates its functional design, including data management subsystem and data visualization subsystem. Secondly, a prediction model of unmanned ship maritime risk based on gray mutation is proposed, by predicting risk mutation location, mutation direction, mutation time, risk causation ability and risk causation efficiency factors. The results show that the risk of unmanned ship is mainly concentrated in the waters from 3+000 to 8+000, and the risk of unmanned ship grounding is mainly concentrated in the outer waters of the main channel from 12+000 to 18+000 and the shallow waters north of the main channel from 6+000 to 12+000. This study proposes a new unmanned vessel maritime safety risk prediction method from a digital health perspective, which provides useful guidance for research and practice in related fields.