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

Purpose: The 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/approach: The 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. Findings: In 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/value: 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. The experimental analysis depicts that proposed algorithm has high accuracy rate, less execution time and error rate.