Evidence map›Paper›PMID 37299864›Full record

ReviewSensors (Basel, Switzerland)2023

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

Shereen Ismail, Hassan Reza, Khouloud Salameh, Hossein Kashani Zadeh, Fartash Vasefi

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Casting light on the workings of illegal fishing markets.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Review
  3. Review
  4. Review
  5. Review
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Shereen IsmailSchool of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND 58202, USA.ORCID 0000-0001-8580-1648
Hassan RezaSchool of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND 58202, USA.ORCID 0000-0002-7593-9624
Khouloud SalamehDepartment of Computer Science and Engineering, American University of Ras Al Khaimah, Ras Al Khaimah 72603, United Arab Emirates.
Hossein Kashani ZadehDepartment of Mechanical Engineering, University of North Dakota, Grand Forks, ND 58202, USA.
Fartash VasefiSafetySpect Inc., 10100 Santa Monica Blvd., Suite 300, Los Angeles, CA 90067, USA.

Funding

NOAA SBIR NA21OAR0210305
6 · The paper itself

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.

Indexed as

BlockchainFish ProductsInternet of ThingsAnimalsFood Industryanti-fraudBlockchainfish supply chainInternet of Thingsmachine learningsecuritytraceability

Identifiers

PMID37299864
PMCPMC10255790

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.