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收储粮食质量安全风险预警平台创建
引用本文:刘美辰,郭 健,耿健强,呙 琴.收储粮食质量安全风险预警平台创建[J].粮油食品科技,2024,32(1):113-119.
作者姓名:刘美辰  郭 健  耿健强  呙 琴
作者单位:北京市食品检验研究院(北京市食品安全监控和风险评估中心),北京 100094;北京国家粮食交易中心,北京 100054
摘    要:基于北京市储备粮各承储企业对粮食中真菌毒素及重金属的快速检测的数据,采用浏览器/服务器(B/S)架构,终端浏览器(WEB),通过加密算法,利用快检设备的无线传输功能对数据进行采集和传输,实现了监测数据的实时迁移;利用点到多点网络通信(P2MP),多设备在线/离线采集的数据通过文件上传系统及关系型数据库抽取工具,实现多源数据同步整合;使用关系型数据库(MySQL)、列式存储数据库(HBase)和分布式文件系统(HDFS)、分布式全文搜索(ElasticSearch)和分布式内存数据库(Redis)实现云储存;使用Storm进行实时计算,Streaming进行流运算,Spark进行内存运算,MapReduce进行批量运算,实现监测数据快速处理;使用人工智能技术及MLlib/Mahout进行数据挖掘建模,形成北京粮源地产区时空序列模型和粮食购销企业信用评价模型,从而实现北京地区粮食质量安全的动态预警和数据可视化表达,提供预警判据,便于管理部门实时掌控、实时响应和粮食质量安全追溯,促进粮食流通和收储领域参与方的良性竞争和诚信体系的建立,为政府决策提供科学依据。

关 键 词:风险预警  粮食  快速检测  信息化  质量安全

Creation of an Early Warning Platform for Risks to the Quality and Safety of Stored Grain
LIU Mei-chen,GUO Jian,GENG Jian-qiang,GUO Qin.Creation of an Early Warning Platform for Risks to the Quality and Safety of Stored Grain[J].Science and Technology of Cereals,Oils and Foods,2024,32(1):113-119.
Authors:LIU Mei-chen  GUO Jian  GENG Jian-qiang  GUO Qin
Abstract:Based on the fast detection of mycotoxins and heavy metals in grain by each storage enterprise of Beijing reserve grain, the real-time migration of monitoring data is realized by adopting the B/S architecture, terminal WEB browser, and using the wireless transmission function of the rapid detection equipment to collect and transmit the data through the encryption algorithm; by using P2MP point-to-multipoint network communication, the data collected by multiple devices online/offline are uploaded through the file uploading system and the relational database extraction tool to achieve synchronous integration of data from multiple sources; by using relational database MySQL, column storage database HBase and distributed file system HDFS, distributed full-text search ElasticSearch and distributed memory database Redis to achieve cloud storage; by using Storm for real-time computation, Streaming for streaming operation, Spark for memory computing, and MapReduce for batch computing to achieve rapid processing of monitoring data; by using artificial intelligence technology and MLlib/Mahout for data mining and modelling to form a spatial and temporal sequence model of Beijing''s grain producing areas and credit evaluation model of grain purchasing and marketing enterprises, so as to achieve the dynamic early warning of grain quality and safety and visual expression of the data, and provide early warning judgments to facilitate real-time control by government departments and real-time response to the situation. It promotes real-time control, real-time response and traceability management of grain quality and safety by management departments, enhances healthy competition and the establishment of an integrity system in grain circulation and storage, and provides a scientific basis for government decision-making.
Keywords:risk early warning  grain  fast detection  information technology  quality safety
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