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IJSTR >> Volume 9 - Issue 3, March 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Iot Based Supply Chain Traceability Using Enhanced Naive Bayes Approach For Scheming The Food Safety Issues

[Full Text]






Bayesian networks, Traceability, Food supply chain management system, Classifier, Naive Bayes, Food safety and Internet of Things (IoT).



Food is one of the major needs for human to live. The worldwide food issue consists of the need of food provision for the Earth's population. Food has to undertake numerous troubles like changing climate, food safety, low nutritive value, etc. Due to the rising demand for fruits and vegetable for daily procedure by the consumers there is necessitate for smarter operation of Food Supply Chain(FCS) and also bond the producer to the customer with delivery of high quality of food products. This paper examines the design and improvement of an Internet of Things (IoT) construction that helps suppliers to manage their procedures of food safety and also tackle the food safety problems from the technological aspect, people require a trustworthy food traceability system that can follow and observe the full lifespan of food manufacture, counting the processes of food raw material farming/reproduction, processing, transporting, warehousing, and wholesale etc. The most important goal of this IoT outline is to sense food characteristics and guidance suppliers to insist farmers properly grow and treat the crops. Using the analysis of fictional data for FSC, deriving a solution for the distribution of distinguished goods with the aid of the Naive Bayes classifier which is used for food traceability enables tracking and management throughout the entire process such as manufacturer, exporter and customer. The structure organizes a collection of IoT nodes arranged in the transporting for sensing food parameters and the RF communication of IoT node is used to transmit the measured data to server. The experimental study of the proposed technique is measured based on time of execution, comparison of accuracy, and rate of error. Prospective strategies were experimented with using the RStudio IDE as the working platform with Java.



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