Journal:A blockchain-driven IoT-based food quality traceability system for dairy products using a deep learning model
| Full article title | A blockchain-driven IoT-based food quality traceability system for dairy products using a deep learning model |
|---|---|
| Journal | High-Confidence Computing |
| Author(s) | Manisha, Noothi; Jagadeeshwar, Madiraju |
| Author affiliation(s) | Chaitanya Deemed to be University |
| Primary contact | noothimanisha6 at gmail dot com |
| Year published | 2023 |
| Volume and issue | 3(3) |
| Article # | 100121 |
| DOI | 10.1016/j.hcc.2023.100121 |
| ISSN | 2667-2952 |
| Distribution license | Attribution-NonCommercial-NoDerivs 4.0 International |
| Website | https://www.sciencedirect.com/science/article/pii/S2667295223000193 |
| Download | https://www.sciencedirect.com/science/article/pii/S2667295223000193/pdfft (PDF) |
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Abstract
Food traceability is a critical factor that can ensure food safety while enhancing the credibility of the manufactured product, thus achieving heightened user satisfaction and loyalty. The perishable food supply chain (PFSC) requires paramount care for ensuring quality owing to the limited product life. The PFSC comprises of multiple organizations with varied interests and is more likely to be hesitant in sharing the traceability details among one another owing to a lack of trust, which can be overcome by using blockchain. In this research, an efficient scheme using a blockchain-enabled deep residual network (BC-DRN) is developed to provide food traceability for dairy products. Here, food traceability is determined by using various modular tools, like the internet of things (IoT), blockchain data management, food traceability blockchain architecture, and DRN-based food quality evaluation tools. The devised BC-DRN-based food quality traceability system is examined based on performance metrics such as sensitivity, response time, and testing accuracy, and it has attained better values of 0.939, 109.564 s, and 0.931, respectively.
Keywords: perishable food supply chain, blockchain, internet of things, food traceability, deep learning
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This presentation is faithful to the original, with only a few minor changes to presentation and updates to spelling and grammar (including to the title). In some cases important information was missing from the references, and that information was added. No other changes were made in accordance with the "No-Derivatives" portion of the distribution license.
