# Integrating Blockchains with the IoT: A Review of Architectures and Marine Use Cases
## 1 Introduction  
The rapid advancement in digital technologies is reshaping the way industries operate, with the Internet of Things (IoT) playing a central role in this transformation. The IoT connects various devices within a unified network, enabling them to share data in real time and make autonomous decisions, creating more responsive and intelligent environments ([PERSON] et al. [1]). This impact is especially prominent in sectors such as healthcare, manufacturing, energy, and transportation, where IoT solutions drive significant progress ([PERSON] et al. [2], [PERSON] and [PERSON] [3]). Nevertheless, despite its widespread adoption, the IoT still faces several challenges that are associated particularly with scalability, resource management, data integrity, and security [4, 5, 6]. This is largely due to many IoT systems relying on centralized architectures, which often struggle to meet the growing demand for real-time processing and secure data management [7]. In this context, blockchain technology offers a potential solution by providing a decentralized and immutable ledger, enhancing the security and integrity of IoT systems. This integration, referred to as the \"Blockchain-enabled IoT\" (BIoT), combines the benefits of the blockchain's decentralized framework with IoT's connectivity, ensuring a more transparent and trustworthy exchange of information [8, 9, 10, 11, 2]. The BIoT's potential is especially evident in demanding marine environments, where it can address challenges that traditional IoT systems fail to manage effectively. Consequently, the unique requirements of these environments have driven the development ofspecialized IoT branches, including the Marine Internet of Things (MIoT) and the Internet of Underwater Things (IoUT). These two subsets extend the reach and capabilities of the IoT to distinct domains, such as ocean monitoring, naval operations, environmental protection, and resource management [13; 14; 15]. However, these domains also pose unique challenges including harsh conditions, a limited communication bandwidth, and the need for energy-efficient operations, all of which impose additional burdens that add complexity to the implementation of IoT applications [16; 17]. For instance, underwater communication channels often suffer from high propagation delays and severe attenuation, making stable connectivity difficult to maintain [18]. Although BIoT technology shows great promise [10], integrating blockchains into these environments can introduce new challenges, such as high implementation costs, the need to standardize legacy systems, and the potential to exacerbate existing issues such as high computational demands and energy consumption, all while having to address the pressing need for scalable solutions [9; 19; 20]. [PERSON] et al. [2] categorize the challenges that stem from BIoT systems into two main areas: resource constraints and scalability. More specifically, they note that the lack of sufficient computational power and storage capacity in many IoT devices often makes it difficult to meet the demands of blockchain technology. To address these challenges, numerous scholars have proposed a range of solutions, including energy-efficient frameworks to minimize resource consumption [21; 22], custom consensus protocols tailored to the specific scalability and security needs of marine environments [23; 24; 25], and multi-layered architectures that utilize cloud, fog, or edge computing, or even hybrids of these, to distribute processing tasks and enhance system performance [25; 26]. These strategies often incorporate technologies such as lightweight nodes for BIoT systems, as recommended by [PERSON] and [PERSON] [3]--and edge computing, as suggested by [PERSON] et al. [27] for resource-constrained marine settings. Other solutions leverage decentralized storage systems such as the InterPlanetary File System (IPFS) for secure data management [14; 28] and Artificial Intelligence (AI)-enhanced security measures to strengthen data integrity [28].