Blockchain and big data integration design for traceability and carbon footprint management in the fishery supply chain

Abstract

The utilization of blockchain technology in the fishing industry has been extensively studied and implemented to address issues such as illegal fishing and carbon emissions control. However, integrating blockchain with the vast amounts of data in the fishing supply chain poses significant challenges. Challenges include managing extensive data such as photos or videos for product traceability throughout their lifecycle, compounded by the growing complexity of cross-border trade and market expansion. Additionally, blockchain's storage capacity limitations present hurdles in fully accommodating and comprehensively storing detailed supply data from a complex and expanding supply chain.

While solutions like the Interplanetary File System (IPFS) have been explored for large data storage on the blockchain, this paper proposes a directly integrated blockchain solution tailored for the challenges of fishing with big data. We introduce a novel big data design that preserves blockchain's anonymity and immutability features, addressing storage limitations while maintaining the architecture's purpose. Furthermore, our proposal integrates product supply chain traceability with carbon footprint tracking, enabling comprehensive assessment based on quality, sustainability, and carbon footprint criteria.

Despite the proposed solution needing to be tested in real-life situations, we conducted rigorous testing through simulation, white-box evaluation, and complexity analysis. The results demonstrate the potential of our solution to address challenges faced in fisheries supply chains, providing valuable insights for future practical implementation and validation efforts.