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

Author:

Ismail Shereen1ORCID,Reza Hassan1ORCID,Salameh Khouloud2,Kashani Zadeh Hossein3,Vasefi Fartash4

Affiliation:

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

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

3. Department of Mechanical Engineering, University of North Dakota, Grand Forks, ND 58202, USA

4. SafetySpect Inc., 10100 Santa Monica Blvd., Suite 300, Los Angeles, CA 90067, USA

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.

Funder

NOAA SBIR

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference90 articles.

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3. Food regulation and policing: Innovative technology to close the regulatory gap in Australia;Lindley;J. Consum. Prot. Food Saf.,2022

4. Determining the provenance and authenticity of seafood: A review of current methodologies;Gopi;Trends Food Sci. Technol.,2019

5. Towards a new’fisheries crime’ paradigm: South Africa as an illustrative example;Witbooi;Mar. Policy,2015

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