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迈向智能区块链物联网赋能的鱼类供应链:综述与概念框架

Toward an Intelligent Blockchain IoT-Enabled Fish Supply Chain: A Review and Conceptual Framework.

机构信息

School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND 58202, USA.

Department of Computer Science and Engineering, American University of Ras Al Khaimah, Ras Al Khaimah 72603, United Arab Emirates.

出版信息

Sensors (Basel). 2023 May 28;23(11):5136. doi: 10.3390/s23115136.

Abstract

The fish industry experiences substantial illegal, unreported, and unregulated (IUU) activities within traditional supply chain systems. Blockchain technology and the Internet of Things (IoT) are expected to transform the fish supply chain (SC) by incorporating distributed ledger technology (DLT) to build trustworthy, transparent, decentralized traceability systems that promote secure data sharing and employ IUU prevention and detection methods. We have reviewed current research efforts directed toward incorporating Blockchain in fish SC systems. We have discussed traceability in both traditional and smart SC systems that make use of Blockchain and IoT technologies. We demonstrated the key design considerations in terms of traceability in addition to a quality model to consider when designing smart Blockchain-based SC systems. In addition, we proposed an Intelligent Blockchain IoT-enabled fish SC framework that uses DLT for the trackability and traceability of fish products throughout harvesting, processing, packaging, shipping, and distribution to final delivery. More precisely, the proposed framework should be able to provide valuable and timely information that can be used to track and trace the fish product and verify its authenticity throughout the chain. Unlike other work, we have investigated the benefits of integrating machine learning (ML) into Blockchain IoT-enabled SC systems, focusing the discussion on the role of ML in fish quality, freshness assessment and fraud detection.

摘要

鱼类产业在传统供应链系统中经历了大量的非法、未报告和无管制(IUU)活动。区块链技术和物联网(IoT)有望通过整合分布式账本技术(DLT)来改变鱼类供应链(SC),构建值得信赖、透明、去中心化的可追溯性系统,促进安全的数据共享,并采用 IUU 预防和检测方法。我们已经审查了当前将区块链纳入鱼类 SC 系统的研究工作。我们讨论了传统和智能 SC 系统中的可追溯性,这些系统利用了区块链和物联网技术。我们展示了可追溯性方面的关键设计考虑因素,以及在设计基于智能区块链的 SC 系统时需要考虑的质量模型。此外,我们提出了一个智能区块链物联网赋能的鱼类 SC 框架,该框架使用 DLT 来实现鱼类产品从收获、加工、包装、运输和分销到最终交付的可追溯性。更准确地说,所提出的框架应该能够提供有价值和及时的信息,这些信息可用于跟踪和追溯鱼类产品,并在整个链条中验证其真实性。与其他工作不同,我们研究了将机器学习(ML)集成到区块链物联网赋能的 SC 系统中的好处,重点讨论了 ML 在鱼类质量、新鲜度评估和欺诈检测中的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e78/10255790/b198ac23ff67/sensors-23-05136-g001.jpg

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