The Outlook of Food Industry: Effectual Traceability Practice in Supply Chain Management using Internet of Things

Traceability can be used to improve processes, increase productivity, and ensure the quality and safety of perishable foods. But it's frequently seen as unnecessary red tape and a financial bur-den. Small and medium-sized businesses frequently exhibit this. Since they make up the majority of the food industry, the adoption of traceability systems is relatively sluggish and primarily done to meet legal requirements. In this paper, we propose effective food traceability techniques using the Internet of things and derive a solution for data communication. The improved Naïve Bayes Classifier is developed for food traceability using the enhanced prediction data. The purpose of the food traceability is used to maintain the computerization, reduced cost and reasonable system complexity. The most important parameter for this system is the food transportation from the manufacturer to the consumer. The Internet of Things is developed to connect the manufacturer to the consumer with an efficient transportation system. An economical solution is achieved using the IoT based food traceability. The Naïve Bayes Classifier is simulated and the investigational results proved that the proposed algorithm is more efficient for food traceability techniques compared to the SVM and KNN methods.