Improvement of C5.0 algorithm using internet of things with Bayesian principles for food traceability systems

• Published in: Modern supply chain research and applications 2021-01, Vol.3 (1), p.2-23
• Main Authors: Souprayen, Balamurugan, Ayyanar, Ayyasamy, K, Suresh Joseph
• Format: Article
• Language: English
• Subjects: Algorithms; bayes theorem; bayesian posterior theory; Big Data; c5.0; Communication; Data compression; Data mining; Data processing; Decision making; Embedded systems; Food quality; Food safety; Food supply; food supply chain; Internet of Things; Machine learning; Sensors; Social research; Supply chains; traceability; verification strategies
• ISSN: 2631-3871; 2631-3871
• DOI: 10.1108/MSCRA-07-2020-0019

PurposeThe purpose of the food traceability is used to retain the good quality of raw material supply, diminish the loss and reduced system complexity.Design/methodology/approachThe proposed hybrid algorithm is for food traceability to make accurate predictions and enhanced period data. The operation of the internet of things is addressed to track and trace the food quality to check the data acquired from manufacturers and consumers.FindingsIn order to survive with the existing financial circumstances and the development of global food supply chain, the authors propose efficient food traceability techniques using the internet of things and obtain a solution for data prediction.Originality/valueThe operation of the internet of things is addressed to track and trace the food quality to check the data acquired from manufacturers and consumers. The experimental analysis depicts that proposed algorithm has high accuracy rate, less execution time and error rate.