Information Traceability And Assistant Decision System For Food Safety

Food safety is a matter of national importance and has always been a matter of great importance to governments at all levels and their regulatory authorities.Especially when it comes to major events such as the Xi’an National Games and the Beijing Winter Olympics,the guarantee of food safety becomes even more important.However,the current problems of food chain information traceability can be summarized as follows: 1.The degree of informationization of the whole chain collection is low,resulting in incomplete access to traceability information;2.It is difficult to guarantee the security of traceability information,and there are problems such as information tampering and forgery;3.The existing traceability system is poor in intelligence,lacks further mining and utilization of traceability information,and the risk monitoring and early warning consideration of the whole chain link is not perfect.It is difficult to provide corresponding auxiliary decision-making information to public security,police and other relevant supervisors before the occurrence of accidents.Therefore,to address the above problems,this paper will build a blockchain-based food safety information traceability and auxiliary decision-making system,and the main research contents are as follows:(1)To address the problem that it is difficult to guarantee the security and reliability of traceability information storage.In this paper,we design a security model of food traceability system composed of multi-organization and multi-nodes based on Fabric framework.The data storage mechanism of "Fabric+Mysql" is proposed,and the ciphertext information is stored in Mysql database,while the key information of each link is uploaded to blockchain through reasonable deployment of chain code.It realizes the security and reliability of information storage in each circulation link and solves the problem of low throughput efficiency of blockchain information storage.(2)Research on artificial intelligence-based food safety assisted decision-making method.Based on the Scrapy framework,we designed a crawler system to collect the original data of food sampling and inspection;constructed an abnormal recognition model of logistics trajectory based on the ST-DBSCAN algorithm to realize the early warning of path deviation and transportation timeout;realized the adaptive recognition and content extraction of uploaded quality inspection reports based on OCR technology;finally,based on the Apriori algorithm,we correlated historical problems and sampled food products to establish a knowledge base.Finally,we establish a knowledge base based on Apriori algorithm to correlate historical problems and sampled foods,and complete the construction of food expert system.(3)Design and implementation of food traceability management platform.This paper realizes the general design and function development of food traceability management platform and terminal operation based on Spring Boot and We Chat applet.The QR-Code is used to realize the "one thing,one code" for food information traceability.It provides system management,food information management,logistics and transportation management,risk warning management and other functions for operators and supervisors.In view of the risk points in each link,we propose to design and implement the corresponding risk warning algorithm model,and integrate it into the traceability management platform in the form of Web Service interface to realize dynamic risk warning in the process of whole-chain food traceability,so as to provide relevant supervisors with auxiliary decision-making information to do a good job in the prevention of food safety risks beforehand and traceability afterwards.