An IoT-Based Cloud Data Platform with Real-Time Connecting Maritime Autonomous Surface Ships

Abstract

Maritime Autonomous Surface Ships (MASS) pose numerous challenges and complexities regarding risk, stability, and implementation. To overcome these obstacles and realize the vision of MASS, the development of an onshore data platform capable of real-time monitoring and support for ship conditions becomes imperative. In this paper, we design a cloud-based data platform that facilitates seamless interaction between ships and onshore through the utilization of IoT technology. To achieve this, we introduce a comprehensive six-layer structure that serves as the foundation of the platform, enabling effective communication and data exchange at each layer. Furthermore, we propose a methodology that leverages data sharing among neighboring ships through the platform, thereby enhancing collision avoidance performance. To implement this methodology, we introduce the architecture of Edge in the structure of MSA and propose an MQTT-based communication method designed to enhance real-time under unstable network conditions. To validate our approach, we implement and test the data platform using AWS Cloud. The simulation results show that the proposed MQTT communication method effectively limits real-time data delay and reduces total data transmission time by 34.6% compared to conventional methods.