(untitled) (Informatica, 2024)
The widespread utilization of Internet of Things poses more and more challenges and opportunities for enterprise supply chain management. This study proposes a method of integrating data mining and Internet of Things management technology for enterprise supply chain information management. By collecting and analyzing a large amount of data generated by Internet of Things devices, real-time and accurate information on supply chain management can be provided, thereby helping enterprises achieve supply chain optimization and collaborative management. This study introduces the architecture and implementation method of a supply chain information management system that integrates data mining and Internet of Things management, and verifies the effectiveness of this method through case analysis. The experiment showed that the average accuracy of the enterprise supply chain information management system was 93.14%, the average sensitivity was 91.05%, and the average specificity was 91.89%. The average error rate was 7.06%, the average delay time was 0.84s, and the average accuracy was 93.21. This indicates that the performance of the enterprise’s supply chain information management data system is excellent, and this method has important application value in improving supply chain efficiency and accuracy.