Prediction Method Research And System Realization Of Temperature And Humidity In Cold Chain Transportation Environment

In the process of cold chain transportation,the temperature and humidity environment of the refrigerated compartment is an important factor affecting the quality of fresh food,and there is a complex coupling relationship between the influencing factors,so that the current cold chain monitoring system can only monitor the environmental parameters in the compartment,but cannot.Predicting the changing trend of the environment cannot meet the actual needs of cold chain transportation.It is of great practical significance to promote the intelligent management of cold chain transportation in my country to carry out research on the prediction of temperature and humidity in cold chain transportation compartments and realize the prediction of temperature and humidity in cold chain transportation compartments.This paper takes the temperature and humidity in the refrigerated compartment as the research object,and studies the temperature and humidity prediction method and prediction system of the cold chain environment.The details are as follows:1.The temperature and humidity data acquisition system of cold chain transportation environment is designed.The refrigerated truck of Xingye Group in Zhoushan City,Zhejiang Province was selected to carry out experimental research.The transported goods were aquatic products such as Zhoushan hairtail and swimming crab.The transportation route was: Zhoushan City,Zhejiang Province to Daxing District,Beijing.According to the data collection requirements,the cold chain transportation remote monitoring system is designed and developed,including three parts: temperature and humidity collection node,vehicle terminal,and remote monitoring platform.Real-time acquisition of temperature and humidity distribution data in refrigerated compartments and real-time positioning and tracking of refrigerated trucks are realized,so as to monitor the whole process of cold chain transportation,and provide a good data foundation for the research of cold chain environmental temperature and humidity prediction models and the development of prediction systems.2.Build a prediction model based on k-medoids algorithm combined with Long and short term memory network.First,use the k-medoids algorithm to fuse the temperature and humidity in the refrigerated compartment,input the fused data into the Long and short term memory network for prediction,and build a temperature and humidity prediction model based on the k-medoids algorithm combined with the Long and short term memory network.Prediction of temperature and humidity changes in the cold chain environment.3.Developed a cold chain transportation environment temperature and humidity prediction system and carried out experimental verification.On the basis of algorithm research,the k-medoids algorithm and Long and short term memory network model are transplanted into the vehicle terminal of the cold chain transportation remote monitoring system,and the operation mechanism of periodic call is adopted to design and implement the cold chain transportation environment temperature and humidity prediction system.The test results show that the system can accurately obtain the changing trend of temperature and humidity in the refrigerated compartment,and the application of the system can realize the intelligent management of the cold chain logistics process.