Food Traceability System Using Blockchain and QR Code

Mishra, Narendra Kumar; Mistry, Sagar; Choudhary, Santosh Kumar; Kudu, Sumukh; Mishra, Rupesh Kumar

doi:10.1007/978-981-15-4542-9_4

Cited by 14 publications

(5 citation statements)

References 4 publications

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“…This necessitates the development of technology that gives consumers the capacity to automatically retrieve the relevant expiry/best before the date, and the ability to trace the origin of the food they purchased across the supply chain. Even though the existing techniques [19][20][21] offered improved benefits, they often fail to incorporate efficient deep learning techniques or explainable AI for efficient decision-making. The efficient traceability of food supply chains is the only issue that is addressed by all the existing BT frameworks [22,23], which do not address technical solutions to improve consumer access to food traceability so that they can verify and track the food they have purchased, possibly using a mobile phone.…”

Section: Related Workmentioning

confidence: 99%

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

Bhatia

Albarrak

2023

Sustainability

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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.

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Section: Related Workmentioning

confidence: 99%

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

Bhatia

Albarrak

2023

Sustainability

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“…Recalls of agri-products due to safety and sanitation issues have been never-ending, leading to the increasing concern about food safety and questions about the quality of the agri-products that enter the market. If not addressed, this issue will debilitate consumer trust in the food markets [38]. Even more, with the growing world population, the need and demands of the food market are not sufficiently met.…”

Section: Discussionmentioning

confidence: 99%

Emerging Crop Traceability Systems in Smart Farming: A Review

Mohamad¹,

King²,

Riza³

et al. 2022

Proceedings of the International Conference on Computer, Information Technology and Intelligent Computing (CITIC 2022)

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Traceability is the ability to retrieve the history, use, location or activity of an identified item, hence crop traceability system is a system that provides unique identification to the crop and tracks all information from the seed until the end product in the market. Crop traceability is beneficial to agri-business owners, farmers and consumers as it enables the production of quality crops. This paper aims to study the emerging crop traceability technologies in smart farming and present the possible solutions to improve the crop traceability system based on the ICT perspective. Some of the technologies involved are barcode, QR code, RFID, IoT, artificial intelligence and blockchain. Among these technologies, blockchain is seen to be the future technology suitable to improve the crop traceability system. However, the integration of blockchain into the existing system is still in the infancy stage.

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“…In the framework for transparency, there is a need to determine the source of the problem by monitoring the products and processes backwards when any undesired situation occurs. Furthermore, it is an approach that aims to establish the necessary information system for crisis management mechanisms such as forward monitoring and recovery (Mishra et al, 2020). Thanks to the traceability, the principles of transparency and traceability provide improvements such as food safety, prevention of food fraud, and food quality (Charlebois & Haratifar, 2015).…”

Section: Case Study and Findingsmentioning

confidence: 99%

A Framework for Evaluating Information Transparency in Supply Chains

Ada

Sağnak

Kazançoğlu

et al. 2021

Journal of Global Information Management

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Private, public, profit, and non-profit organizations, and society as a whole currently face a significant reliable information necessity problem. Especially supply chains need trustworthy information to perform their activities successfully. This study aims to propose a framework and identify how reliability of information can be evaluated and measured through the concept of transparency. In this context, dimensions such as; comprehensiveness, regularity, timeliness, content, scope, and user-friendliness are the pillars of the proposed framework. Selected criteria have been used as inputs to develop the information transparency level. The Fuzzy Analytic Network Process (ANP) is used to obtain weights of these inputs, and Data Envelopment Analysis (DEA) is used for the determination of the efficiency ranking for transparency. Results demonstrated that Content, Scope and Comprehensiveness dimensions have 75% impact on the transparency of data. Remaining 25 percent is affected by Timeliness, Regularity and User-friendliness.

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Food Traceability System Using Blockchain and QR Code

Cited by 14 publications

References 4 publications

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

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

Emerging Crop Traceability Systems in Smart Farming: A Review

A Framework for Evaluating Information Transparency in Supply Chains

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