{"title":"基于深度学习模型的BC驱动的基于物联网的乳制品食品质量追溯系统","authors":"Noothi Manisha, Madiraju Jagadeeshwar","doi":"10.1016/j.hcc.2023.100121","DOIUrl":null,"url":null,"abstract":"<div><p>Food traceability is a critical factor that can ensure food safety for enhancing the credibility of the product, thus achieving heightened user satisfaction and loyalty. The Perishable Food SC (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 (BC). In this research, an efficient scheme using BC-Deep Residual Network (BC-DRN) is developed to provide food traceability for dairy products. Here, food traceability is determined by using various modules, like the Internet of Things (IoT), BC data management, Food traceability BC architecture, and DRN-based food quality evaluation modules. The devised BC-DRN-based food quality traceability system is examined based on its performance metrics, like sensitivity, response time, and testing accuracy, and it has attained better values of 0.939, 109.564 s, and 0.931.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"BC driven IoT-based food quality traceability system for dairy product using deep learning model\",\"authors\":\"Noothi Manisha, Madiraju Jagadeeshwar\",\"doi\":\"10.1016/j.hcc.2023.100121\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Food traceability is a critical factor that can ensure food safety for enhancing the credibility of the product, thus achieving heightened user satisfaction and loyalty. The Perishable Food SC (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 (BC). In this research, an efficient scheme using BC-Deep Residual Network (BC-DRN) is developed to provide food traceability for dairy products. Here, food traceability is determined by using various modules, like the Internet of Things (IoT), BC data management, Food traceability BC architecture, and DRN-based food quality evaluation modules. The devised BC-DRN-based food quality traceability system is examined based on its performance metrics, like sensitivity, response time, and testing accuracy, and it has attained better values of 0.939, 109.564 s, and 0.931.</p></div>\",\"PeriodicalId\":100605,\"journal\":{\"name\":\"High-Confidence Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2023-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"High-Confidence Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2667295223000193\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"High-Confidence Computing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667295223000193","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
BC driven IoT-based food quality traceability system for dairy product using deep learning model
Food traceability is a critical factor that can ensure food safety for enhancing the credibility of the product, thus achieving heightened user satisfaction and loyalty. The Perishable Food SC (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 (BC). In this research, an efficient scheme using BC-Deep Residual Network (BC-DRN) is developed to provide food traceability for dairy products. Here, food traceability is determined by using various modules, like the Internet of Things (IoT), BC data management, Food traceability BC architecture, and DRN-based food quality evaluation modules. The devised BC-DRN-based food quality traceability system is examined based on its performance metrics, like sensitivity, response time, and testing accuracy, and it has attained better values of 0.939, 109.564 s, and 0.931.