In a significant stride towards modernizing maritime traffic management, researchers have developed an intelligent system that combines distributed blockchain technology with federated reinforcement learning to enhance collaborative decision-making in ship traffic supervision. The study, led by Zhang Wei from the School of Maritime at Jiujiang Polytechnic University of Science and Technology, was recently published in the journal *Scientific Reports* (which translates to *Scientific Reports* in English).
Traditional maritime traffic monitoring systems often grapple with data silos, privacy concerns, and centralized decision-making bottlenecks that hinder effective coordination among multiple jurisdictions. The new framework addresses these challenges by employing a multi-layered architecture that includes a data layer, blockchain layer, federated learning layer, and decision layer. This setup enables secure data sharing while preserving the operational autonomy of maritime authorities.
The distributed blockchain mechanism ensures data integrity and immutability through cryptographic protocols and smart contracts. Meanwhile, the federated reinforcement learning algorithm allows for privacy-preserving collaborative model training without exposing sensitive commercial information. According to the study, the system achieved a decision accuracy of 93.6%, an average response time of 520 milliseconds, and a throughput of 285 transactions per second.
Zhang Wei explained, “Our framework ensures data integrity and immutability through cryptographic protocols and smart contracts, while the federated reinforcement learning algorithm enables privacy-preserving collaborative model training without exposing sensitive commercial information.”
Case studies involving emergency collision avoidance, abnormal behavior identification, and search-and-rescue coordination demonstrated the system’s practical effectiveness. The research reported a 40% reduction in incident response times and a 60% enhancement in cross-agency collaboration efficiency.
For the maritime industry, this innovation presents substantial commercial opportunities. Enhanced collaborative decision-making can lead to more efficient traffic management, reduced incident response times, and improved safety. The system’s ability to preserve privacy while sharing data can foster greater trust and cooperation among maritime authorities, ultimately benefiting the entire sector.
As the maritime industry continues to evolve, the integration of advanced technologies like blockchain and federated learning could set new standards for traffic supervision and safety. The research provides a robust foundation for next-generation maritime traffic management systems that require secure multi-party collaboration and intelligent decision optimization.