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A Blockchain-Driven Food Supply Chain Management Using QR Code and XAI-Faster RCNN Architecture

Author

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  • Surbhi Bhatia

    (Department of Information Systems, College of Computer Science and Information Technology, King Faisal University, Al-Ahsa 31982, Saudi Arabia)

  • Abdulaziz Saad Albarrak

    (Department of Information Systems, College of Computer Science and Information Technology, King Faisal University, Al-Ahsa 31982, Saudi Arabia)

Abstract

The availability of food in a country and the capacity of its citizens to access, acquire, and receive enough food are both referred to as having food security. A crucial component of food security is ensuring and maintaining safe and high-quality goods, which the supply chain process should take into due deliberation. To enhance the food supply chain, organic and wholesome food items should be encouraged. Although packaged goods are evaluated and approved by legal authorities, there is no mechanism in place for testing and assessing the market’s available supply on a regular basis. As a result, food manufacturers are compelled to provide nutritious and healthy products. In this research, we propose an explainable artificial intelligence-based faster regions with convolutional neural networks (XAI-based Faster RCNN) model to evaluate the contents of the food items through user-friendly web-based front-end design and QR code. To validate each communication token in the network, an elliptic curve integrated encrypted scheme (ECIES) based on blockchain technology is utilized. Additionally, artificial rabbit optimization (ARO) is used to register each user and assign him a key. The user will gain a deeper understanding of machine learning (ML) and AI applications using the XAI technique. An EAI-based Faster RCNN model is proposed to help digitize information about food products, rapidly retrieve the information, and discover any hidden information in the quick response (QR) code that could have impacted the safety and quality of the food. The results of the experiments indicated that the proposed method requires less response time than other existing methods with the increase of payload and users. The Shapley additive explanation is used to obtain a legal plea for the laboratory test based on the nutritional information present in the QR code. The benefits provided by ECIES-based blockchain technology assist policymakers, manufacturers, and merchants in efficient decision-making, minimizing public health hazards, and improving welfare. This paper also shows that the accuracy achieved by the proposed method reached 99.53%, with the lowest processing time.

Suggested Citation

  • Surbhi Bhatia & Abdulaziz Saad Albarrak, 2023. "A Blockchain-Driven Food Supply Chain Management Using QR Code and XAI-Faster RCNN Architecture," Sustainability, MDPI, vol. 15(3), pages 1-16, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2579-:d:1053127
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    References listed on IDEAS

    as
    1. Hu, Hui & Xu, Jiajun & Liu, Mengqi & Lim, Ming K., 2023. "Vaccine supply chain management: An intelligent system utilizing blockchain, IoT and machine learning," Journal of Business Research, Elsevier, vol. 156(C).
    2. Somdip Dey & Suman Saha & Amit Kumar Singh & Klaus McDonald-Maier, 2021. "FoodSQRBlock: Digitizing Food Production and the Supply Chain with Blockchain and QR Code in the Cloud," Sustainability, MDPI, vol. 13(6), pages 1-11, March.
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    Cited by:

    1. Basim Aljabhan & Muath A. Obaidat, 2023. "Privacy-Preserving Blockchain Framework for Supply Chain Management: Perceptive Craving Game Search Optimization (PCGSO)," Sustainability, MDPI, vol. 15(8), pages 1-23, April.

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