Block Chain Integration with AI for Agriculture Product Supply Chain

Uike D.; Villavicencio-Mendoza M.; Gehlot A.; Verma D.; Panduro-Ramirez J.; Susanto E. · Proceedings of the 2022 11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022 (2022) · DOI: 10.1109/smart55829.2022.10047358

Resumen

Customers spend for agro - based items made by farmers in agro - based supply chain operations (ASCs). People stress the significance of agri-food quality throughout this operation, while producers anticipate higher revenues. Effective tracing and governance for agri-food commodities encounter enormous hurdles as a result of the size and dynamism of ASCs. Nevertheless, the majority of the currently available solutions are unable to adequately address the accountability and administration needs of ASCs. First, in order to enable product tracing and provide organizational unit for the agri-food tracking data in ASCs, we develop a blockchain-based ASC architecture. The manufacturing and preservation of agri-food goods are then effectively decided in order to maximize profit using a Learning Based training-based Supply Chain Administration technology. To show the efficiency of the suggested cryptocurrency system and the DR-SCM approach in various ASC contexts, detailed simulation tests are conducted. The findings indicate that the proposed ledger ASC architecture provides a strong assurance of trustworthy product traceability. Moreover, compared to intuitive and Q-learning approaches, the DR-SCM may provide larger product profitability.

Instituciones: Universidad de San Martín de Porres