A Food Traceability System Based on Blockchain and the Random Forests Algorithm - Shi, Wei (2020)
The frequently happened food scandals worldwide and the outbreak of CODIV-19 have led to increasing concern regarding food quality and safety issues. Providing a food traceability system seems to be a basic requirement. However, most food traceability systems are criticized that customers cannot verify the authenticity of the information provided by companies regarding the origin of and the shipment of purchased products. With extensive research on Blockchain technology, it is believed that it has the potential to tackle the problem of validating data for customers. This study aimed to propose a blockchain-enabled food traceability system for the agricultural sector in China. Furthermore, we investigate the applicability of the random forests algorithm, one of the machine learning techniques, in the design of the system. The random forests algorithm is believed to further enhance the effectiveness of the proposed system with an automatic data validation process to concern the data of agricultural products and classify them to their quality levels. The anticipated result of this proposed system is expected to be effective to evaluate the quality of agricultural products at every stage to reduce the occurrence of food quality and safety issues and provide authentic information to customers and involved parties in the agricultural supply chain.