A relatively new piece of blockchain-based software called a food monitoring system seeks to aid in the fight against fraud. In terms of utility, flexibility, and reliability, a large number of the systems now in use in the food processing industry are insufficient. This supply chain link therefore requires a lot of time because it adds more complexity. Blockchain technology offers a new concept that is crucial to resolving the previously described issues when it comes to the supply chain system that is presently being built and used.
The model presented in this abstract combines state-of-the-art advancements in blockchain machine learning (ML) with a fuzzy logic monitoring system that is layered on top of ashelf-life management system to create a blockchain- and machine learning-based food tracing system for handling perishable food. In this instance, the method would be applied to identify potentially contaminated food products. The suggested solution uses blockchain technology to help solve a number of issues, including bulk condensation loss, storage area requirements, and transit times. AI can manage the intricacy of product monitoring as data will be transferred across a network securely. Finally, the supply chain can make use of a precise and trustworthy data management chain to lengthen the entire flow of the system.
Author Contributions
Conceptualization and methodology, A.B.G., V.B.G. and M.S.B.; software, A.B.G., V.B.G. and M.S.B.; validation, A.B.G., V.B.G. and M.S.B.; formal analysis, A.B.G.; data curation, A.B.G. and V.B.G.; writing—original draft preparation, V.B.G.; writing—review and editing, M.S.B.; supervision, A.B.G., V.B.G. and M.S.B. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Data is contained within the article.
Conflicts of Interest
The authors declare no conflict of interest.
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