BC driven IoT-based food quality traceability system for dairy product using deep learning model
Noothi Manisha, Madiraju Jagadeeshwar
Abstract
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.