A Real-Time Digital Twin Framework Integrating Blockchain, IoT, and Explainable Artificial Intelligence for Secure and Autonomous Maritime Transportation

The rapid digital transformation of maritime transportation has intensified the need for intelligent, cybersecure, and autonomous operational frameworks capable of addressing logistics complexity, environmental uncertainty, fragmented communication infrastructures, and evolving cyber threats. Conventional maritime transportation systems remain limited by poor interoperability among vessel communication networks, port management platforms, cargo monitoring systems, and operational decision-support architectures, resulting in reduced transparency, delayed logistics coordination, increased fuel consumption, and restricted predictive capability. To address these challenges, this study proposes an integrated intelligent maritime transportation framework combining the Internet of Things (IoT), blockchain technology, explainable artificial intelligence (XAI), and real-time digital twin technology within a unified operational ecosystem. The proposed architecture employs distributed IoT sensor networks deployed across vessels, smart ports, cargo containers, and offshore logistics corridors to continuously collect operational, navigational, environmental, and logistics-related data. A decentralized blockchain layer is integrated to provide secure transaction validation, tamper-resistant cargo documentation, smart contract automation, and transparent maritime supply chain coordination. Simultaneously, a hybrid explainable AI framework combining deep learning, reinforcement learning, and SHAP-based interpretability mechanisms is developed for predictive maintenance, autonomous route optimization, cyberattack detection, congestion forecasting, anomaly detection, and fuel-efficiency improvement. The framework further incorporates a continuously synchronized digital twin environment for adaptive operational monitoring and predictive risk assessment. A large-scale simulation environment representing autonomous shipping systems and smart port operations was developed to evaluate the proposed framework under dynamic operational conditions. Comparative analyses demonstrated significant improvements in operational transparency, cybersecurity resilience, predictive reliability, and logistics efficiency. The proposed framework reduced cargo verification delay by ۴۱.۸%, improved cyberattack detection accuracy to ۹۸.۲%, decreased fuel consumption by ۱۸.۶%, and reduced congestion prediction error by ۳۶.۹%. The findings confirm the potential of integrated IoT-blockchain-XAI-digital twin architectures for enabling secure, sustainable, and autonomous next-generation maritime transportation systems.

کلیدواژه ها:

Maritime transportation ، Internet of Things (IoT) ، Blockchain ، Artificial intelligence ، Explainable AI ، Digital twin ، Smart ports ، Autonomous shipping ، Maritime cybersecurity ، Intelligent logistics ، Predictive maintenance ، Sustainable maritime systems ، Deep learning ، Smart contracts ، Port automation ، Maritime supply chain optimization