Blockchain-Integrated AI Systems for Contamination Prediction in Ready-to-Eat Foods: A Systematic Review
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Review Papers | Food Science | Canada | Volume 14 Issue 2, February 2025 | Popularity: 4.8 / 10


     

Blockchain-Integrated AI Systems for Contamination Prediction in Ready-to-Eat Foods: A Systematic Review

Nwanneka Joseph


Abstract: The integration of blockchain and artificial intelligence (AI) technology is an emerging approach to enhancing traceability and contamination prediction in the ready-to-eat (RTE) food industry. This systematic review evaluates the current research on blockchain-integrated AI systems, examining their applications in food safety, supply chain transparency, and contamination risk prediction. A comprehensive analysis of reports, articles, and case studies assesses the effectiveness, challenges, and future prospects of these technologies. The findings highlight blockchain-AI integration as a promising solution for RTE food safety while identifying key gaps in scalability, interoperability, and regulatory compliance. This review provides a framework for future research and practical implementation in the food industry.


Keywords: Food safety, Foodborne illness, Food traceability, Blockchain technology, Contamination prediction, Ready-to-eat foods (RTE), Predictive analytics, Machine learning (ML), Regulatory compliance, Food supply chain


Edition: Volume 14 Issue 2, February 2025


Pages: 772 - 778


DOI: https://www.doi.org/10.21275/SR25212021618



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Nwanneka Joseph, "Blockchain-Integrated AI Systems for Contamination Prediction in Ready-to-Eat Foods: A Systematic Review", International Journal of Science and Research (IJSR), Volume 14 Issue 2, February 2025, pp. 772-778, https://www.ijsr.net/getabstract.php?paperid=SR25212021618, DOI: https://www.doi.org/10.21275/SR25212021618

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