## 2 Maritime Digitalization
Layer 1 solutions include upgrades like modifying block sizes, altering consensus mechanisms like moving to proof-of-stake (PoS), or dividing the network into smaller sections for concurrent processing, i.e., sharding technologies. Layer 2 solutions [30] include rollups via bundling transactions or zero-knowledge proofs (ZKPs), sidechains, off-chain state channels, etc. In contrast, private blockchains are controlled by a central authority, permitting only authorized users to access the blockchain [31]. This centralized control facilitates faster processing speeds, easier network scalability, and the ability to assign different permissions to participants to protect data. Consortium blockchains [32] or federated blockchains represent a hybrid modelthat combines features of both public and private blockchains. Consortium blockchains allow multiple organizations to maintain control over the blockchain network. While network participation is generally open, specific permissions can be granted to certain organizations [33]. The use of smart contracts is one of the critical building blocks for blockchain networks [34; 35]. A smart contract is a decentralized, self-executing contract with the terms of the agreement directly written into code and run on a blockchain. The codes of a smart contract are stored on a blockchain and managed by network consensus for execution as programmed. In the context of smart contracts, Turing completeness means that a smart contract can execute any computational logic or process, allowing developers to create contracts capable of performing complex tasks and implementing intricate logic directly on the blockchain, which paves the way for the development and growth of Web3 applications [36; 37]. The integration of AI and blockchain may eventually help create a collaborative ecosystem with advanced intelligence to enable better efficiency, automation, and security and enhance the quality of services in widespread application domains. Examples of the primary benefits of AI and blockchain synergy are summarized in Table 1. In the maritime sector, the integration of AI and blockchain holds transformative potential to address some of the industry's most pressing challenges and pain points. With the increasing digitization of global supply chains, ports, and shipping networks, the maritime sector has emerged as a prime candidate for leveraging these technologies to improve safety, efficiency, and sustainability. For instance, in port operations, AI can process historical data on vessel arrivals, congestion patterns, and weather conditions to optimize berthing schedules and predict potential delays. Blockchain ensures the reliability of the data sources and systems that produce the operational data, providing a trustworthy foundation for AI models. In global maritime supply chains, AI and blockchain can improve risk management by enabling real-time analysis of global events that may impact maritime operations, such as geopolitical events, cyber threats, port strikes and shipping events like blockage and attacks. This integrated approach enhances resilience across the maritime supply chain, empowering stakeholders to respond promptly to unforeseen events. The integration of AI and blockchain in the maritime sector not only promises increased traffic safety, operational efficiency and transparency but also aligns with broader sustainability goals. This synergy could drive the digital transformation of the maritime sector, positioning it to meet the demands of a complex, interconnected global trade ecosystem. In Figure 4, a representative digital stack structured across several interconnected layers is illustrated for maritime digitalization. The infrastructure layer comprises IoT