AI in Maritime Logistics & Sustainability
From Smart Ports to Sustainable Port Ecosystems: The Transformative Role of Artificial Intelligence
Authors: Marcela Castro, Maria Rosilene Sabino, Maria do Rosário Cabrita, Ana Mendes, Tiago Pinho
Published in Systems 2026, 14, 187. DOI: 10.3390/systems14020187
Ports are critical nodes in global supply chains, pivotal for sustainability. This study analyzes how AI drives sustainable innovation in port ecosystems, focusing on efficiency, transparency, resilience, and environmental performance. Through a systematic screening and bibliometric analysis of 80 articles (2019-2025), we identified three key AI application streams: operational optimization, digital enablement (IoT, data), and governance (Port State Control, cyber-resilience). The research highlights AI's convergence with IoT and blockchain to enhance trust and interoperability. This synthesis uncovers research gaps and future directions for integrated frameworks in sustainable port ecosystems and Sustainable Commerce 4.0.
Executive Impact Snapshot
This research provides critical insights into the evolving landscape of AI-driven sustainability in port operations.
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Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
AI for Operational Efficiency & Safety
Early AI applications significantly improved Estimated Time of Arrival (ETA) prediction, enhancing maritime safety and operational efficiency. Data-driven methods for AIS/LRIT exploitation formed the technical bedrock.
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Citations for Top ETA Prediction Research (2019)
Alessandrini et al. (2019) is the most cited paper on ETA prediction, highlighting early AI impact on core maritime operations.
Business Application: Optimize vessel scheduling, reduce fuel consumption, and improve safety in congested waterways through highly accurate predictive analytics.
Integrated Smart-Port Architectures with AI & IoT
This phase emphasized the integration of AI with IoT and digital twins to create comprehensive smart-port architectures, enabling system-level coordination and real-time decision-making.
Enterprise Process Flow: Smart Port Digital Integration
Data Ingestion (IoT/Sensors)
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AI-Powered Analytics
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Digital Twin Modeling
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Real-time Decision Support
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Integrated Port Operations
Business Application: Develop a holistic digital infrastructure for real-time monitoring, predictive maintenance, and optimized resource allocation across the entire port ecosystem.
AI for Cyber-Physical Resilience & Green Operations
AI adoption broadened to address cyber-physical integration and sustainability, including advanced threat intelligence for IoT-enabled maritime systems and machine learning for green port operations.
| Aspect | Traditional Approach | AI-Enhanced Approach |
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| Cybersecurity |
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| Environmental Monitoring |
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| Structural Health Monitoring |
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Business Application: Implement AI-driven cybersecurity to protect critical infrastructure and leverage AI for continuous environmental optimization, reducing carbon footprint and operational risks.
Governance, Interoperability & Sustainable Commerce 4.0
The latest research focuses on integrating AI with robust governance, interoperability, and blockchain for resilient, transparent port ecosystems, aligning with broader Sustainable Commerce 4.0 objectives.
Case Study: Future Port Governance with AI and Blockchain
A leading port authority faces increasing pressure for transparency and resilience in its global supply chain. By integrating AI-driven predictive analytics with a blockchain-enabled data platform, the port achieves significant advancements:
Enhanced Transparency: Real-time, immutable records of cargo movements, customs clearance, and environmental compliance are accessible to all authorized stakeholders. This reduces disputes and improves trust across the supply chain.
Automated Compliance: AI models automatically flag potential compliance breaches and trigger alerts based on regulatory frameworks, streamlining Port State Control inspections and reducing human error.
Supply Chain Resilience: AI analyzes data from various sources (weather, geopolitical events, traffic) to predict potential disruptions. This data is shared securely via blockchain, enabling coordinated, rapid responses across the port ecosystem to mitigate impacts.
Sustainable Commerce 4.0: The integrated system facilitates the tracking and verification of sustainable practices, such as emissions reductions and green logistics, providing auditable data for environmental reporting and incentivizing eco-friendly operations.
This synergistic approach positions the port as a leader in Sustainable Commerce 4.0, demonstrating how advanced technologies can deliver both economic and environmental value.
Business Application: Design integrated governance frameworks that leverage AI and blockchain for enhanced transparency, compliance automation, and cross-organizational collaboration to build more resilient and sustainable supply chains.
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Your AI Implementation Roadmap
A phased approach to integrate AI into your port operations for maximum sustainable impact.
Phase 1: Pilot & Data Infrastructure Setup (3-6 Months)
Initiate pilot projects for specific pain points (e.g., ETA prediction, anomaly detection). Establish secure data pipelines from IoT sensors and existing systems. Focus on data governance and quality to build a robust foundation for AI.
Phase 2: Core AI Model Development & Integration (6-12 Months)
Develop and train core AI models for operational optimization (e.g., traffic management, resource allocation) and initial environmental monitoring. Integrate models with existing operational technology (OT) systems and conduct rigorous testing in a sandbox environment.
Phase 3: Ecosystem Integration & Scalability (12-18 Months)
Expand AI solutions across more port subsystems. Integrate with external stakeholders (shipping lines, logistics providers) using secure, interoperable platforms (e.g., blockchain). Focus on cyber-physical resilience and adaptive governance frameworks.
Phase 4: Continuous Optimization & Governance (Ongoing)
Implement continuous learning for AI models based on new data and operational feedback. Establish robust governance for ethical AI use, accountability, and regulatory compliance. Drive towards a fully integrated, sustainable port ecosystem model (Sustainable Commerce 4.0).
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