Dynamic Monitoring Of Food Storage Environment Based On Multi-Sensor Information Fusion Technology

With the continuous improvement of the quality of people's daily life,people's pursuit of quality of life has also risen from "full" to "eat well".But in recent years,food quality problems occur frequently,which bring harm to people's physical and mental health.From planting or breeding to people's table,foods need to go through many stages of processing,transportation and so on.Among the many stages of food processing,storage is one of the most easily affected stages of food quality.In order to improve the quality and the safety of the food,this paper devotes to the study of dynamic monitoring of food storage environment.In order to ensure that food does not deteriorate due to the change of environmental factors in the storage process,it can improve the quality of life and reduce unnecessary losses of storage enterprises.The CC2530 development board is used to carry sensors with different functions to acquire storage environment information,and the collected data is uploaded to local servers in real time by using short-range wireless transmission technology.The upper computer is developed by C#language to display the information of storage environment dynamically.In this paper,the processing method of two fusion is proposed by using multi-sensor information fusion technology to process raw data,combined with Kalman filter and BP neural network.The one fusion method is the Kalman filter which is used to fuse the same kind of information collected by different sensors.And the other fusion is the BP neural network which is used to fuse the different kinds of environmental information in order to adjust the storage environment and ensure the quality of food.The simulation test proves that the method above could improve the accuracy and reliability of the data effectively and achieve the goal of the real-time monitoring of food storage environment.