An efficient bayes classifiers algorithm for traceability of food supply chain management using internet of things

Abstract

The conventional Food Supply Chain Management (FSCM) faces a variety of provocation such as ambiguity, security, cost, complication and quality concerns. To resolve these issues, supply chain must be precise. A challenging assignment in today’s food industry is distributing the high quality of foods throughout the supply chain management. In this paper, proposes an efficient Bayes Classifiers Algorithm which integrated with FSCM using Internet of Things (IoT) to allow tracking, tracing and managing the entire process of food supply chain such as supplier, exporter and customers. The objective of this paper is to determine the food safety and to optimize chronological data produced to analyze the effective possibility of future assump-tions. It also aims to foods carrying from the manufacturers to the customers with help of IoT technologies to bond the producer to the customer with delivery of high class of food products. IoT based Food Supply Chain Traceability is utilized t o data transaction effectively with indeterminate, uncertain and insufficient information. So the proposed efficient Bayes Classifiers Algorithm will be capable to overcome all provocation of conventional supply chain and afford secure background and food safety for FSCM process using IoT technology.