System Research And Development Of Grain Condition Data Processing Based On REST Architecture

Stored grain quality and safety are the focus areas of grain storage, grain storage information to provide the data support and technical support, but now common food situation information systems’ s technical complexities, the efficiency is not high, low scalability, long development cycles and it is not strong to develop on Mobile client and other issues, urgent need to establish a suitable data processing grain situation characterized by lightweight, high efficiency, easy expansion and application-oriented model of mobile terminal development, and the development of grain situation data processing system based on this model.This paper studies the server and the mobile client computing based on their respective characteristics, comparison of theoretical and experimental research for two different based SOAP and REST Web Services service system framework is proposed for grain condition data processing system developed mobile client / server(M / S) application model. The Application model based on the REST architecture, the server-side by the data processing module grain situation analysis of relevant information resources processing, the client uses a unified interface method to access the appropriate resources, and data visualization are based on the computing power of different terminals. Highly abstract features of the application of the model, but also for the future treatment of new grain condition information provides greater room for expansion.Demand, the subject of design based on the characteristics of the model and the grain situation management business developed a prototype system in order to verify the M / S application model based on REST architecture advantage in the food situation information systems development. The server end of the prototype system to realize the granary of grain storage temperature predictive analysis and treatment resources, and the mobile terminal data visualization. Among them, the food situation data processing module we use RBF neural network algorithm to predict the temperature of stored grain silo.In this paper, the research background and status of the technology, theory and practice of comparative analysis, the model is determined, system implementation, article summary and expanded bus, the latter can be further expanded and research on this aspect.