Application Research of Computer Artificial Intelligence Technology in Green Cold Chain Logistics of Agricultural Products

In the process of refrigerated transportation, the freshness degree and transportation speed of fresh commodities play a crucial role in improving transportation efficiency and reducing transportation costs. This paper designs an environmental monitoring system for agricultural cold chain logistics based on statistical process control (SPC). C4.5 decision tree was used to classify each link of the supply chain, and it was integrated with the concept of statistical process management to construct a cold chain system suitable for agricultural products. The monitoring system is designed and implemented with LabVIEW to achieve better information sharing. This paper presents an information communication scheme based on cold chain logistics system, and analyzes various testing devices in cold chain logistics system. Through component library and cloud computing technology, independent functional units, remote services and reusable software resources are provided for the cold chain logistics system of fresh agricultural products. Experimental results show that this method has accurate logistics level positioning. Effective discrimination of environmental data, and has a strong quality change inversion ability.