A System Model Integrating Dynamic Analysis and Prediction of Core Technologies of Electric Unmanned Vessels

Electric unmanned vessels (EUVs) are a necessary part of a zero-carbon future of marine transport. There is significant knowledge of driverless technology on the one hand and on electric power on the other. However, less is known of dynamic evolution of core technologies of EUVs and future trends of integration with other technologies. The purpose of this paper is to develop a research pathway for the sustainable development of future EUVs. this paper systematically analyzes the development status, technical bottlenecks and future technical opportunities of EUVs technology. Patents on EUVs are used to mining core technologies with BERT-kmeans and Su-Field model of TRIZ. Dynamic correlations and trends of core technologies under different topics are explored by dynamic social network analysis (DSNA). Finally, by exploring the current state of development of different types of core technologies for EUVs in other domains, the possibility of future convergent technologies is predicted by link prediction. This study discusses what kind of network relationships (e.g., components, core technologies, convergent technologies) need to be understood when studying the field of EUVs. Three directions of technology opportunities for future research are proposed: wireless communication technology, information sensing technology, and renewable energy power supply technology