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

Area of Science:

• Supply Chain Management
• Information Technology
• Food Science

Background:

• Illegal, unreported, and unregulated (IUU) fishing activities pose significant challenges to traditional fish supply chains.
• Existing supply chain systems lack the transparency and security needed for effective traceability and fraud prevention.
• Emerging technologies like Blockchain and the Internet of Things (IoT) offer potential solutions for these issues.

Approach:

• A comprehensive review of current research on integrating Blockchain into fish supply chain systems.
• Discussion of traceability mechanisms in traditional, Blockchain, and IoT-enabled smart supply chains.
• Demonstration of key design considerations for Blockchain-based smart supply chain systems, including a quality model.

Key Points:

• Proposed an Intelligent Blockchain IoT-enabled framework for fish supply chain traceability using distributed ledger technology (DLT).
• The framework enables secure data sharing for tracking and tracing fish products from harvest to final delivery.
• Investigated the integration of machine learning (ML) for fish quality, freshness assessment, and fraud detection within the Blockchain-IoT system.

Conclusions:

• Blockchain and IoT technologies can create trustworthy, transparent, and decentralized traceability systems for the fish industry.
• The proposed framework enhances fish product authenticity verification and combats IUU activities.
• Integrating ML offers advanced capabilities for quality control and fraud detection, further securing the fish supply chain.