基于大数据和QT的农机配件供应链云平台系统设计
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摘要
随着农业现代化水平的不断提高,农业机械被广泛的应用在耕种作业过程中,农机配件的需求量也不断增加,但当前农机配件产品的生产流通环节的监控力度很小,容易造成农机配件的质量安全问题。为了解决这个问题,保证农机配件供应链的可溯源性,基于大数据和QT软件界面开发工具,提出了农机配件供应链数据存储和查询的云平台系统,旨在提高农机配件供应链的数据存储和查询效率,保证农机配件的可溯源性。为了验证平台的可行性,搭建了农机配件供应链的大数据云平台,在平台的底层的Hadoop集群上搭建了8台服务器,以搜索查询农机配件的各种参数数据为测试目的,对平台进行了测试,并将其与传统的MySQL服务器进行了对比。测试结果表明:在搜索数据较少时,云平台和传统服务器的速度相当;但在大数据搜索条件下,云平台的数据处理速度是传统服务器的数倍,从而验证了云平台系统的优越性,为保证农机配件的安全和可溯源性提供了可靠的技术保障。
With the continuously improve the level of agricultural modernization,agricultural machinery is widely used in the farming operation process,demand for agricultural machinery parts are also increasing,but it is very small efforts to monitor the production and circulation of the agricultural machinery accessories products,easy to cause the quality safety problems of agricultural machinery parts. In order to solve this problem,ensure agricultural machinery parts supply chain traceability,it introduced the big data and QT software interface development tool based on the proposed cloud platform system of agricultural machinery parts supply chain data storage and query,thereby improving the agricultural machinery parts supply chain data storage and query efficiency,ensure the traceability of agricultural machinery parts. In order to verify the feasibility of the platform,to build a large data cloud platform of agricultural machinery parts of the supply chain,to build 8 servers in the Hadoop cluster platform at the bottom,to search various parameters of parts of agricultural machinery for testing purposes,the platform is tested,and the traditional MySQL server are compared. The test results indicate that the search in less data,cloud platforms and traditional server speed,but the search conditions in big data,the data processing speed of cloud platform is the traditional server several times,so as to verify the superiority of cloud platform system,in order to ensure the safety of agricultural machinery parts and traceability technology provides reliable guarantee.
With the continuously improve the level of agricultural modernization,agricultural machinery is widely used in the farming operation process,demand for agricultural machinery parts are also increasing,but it is very small efforts to monitor the production and circulation of the agricultural machinery accessories products,easy to cause the quality safety problems of agricultural machinery parts. In order to solve this problem,ensure agricultural machinery parts supply chain traceability,it introduced the big data and QT software interface development tool based on the proposed cloud platform system of agricultural machinery parts supply chain data storage and query,thereby improving the agricultural machinery parts supply chain data storage and query efficiency,ensure the traceability of agricultural machinery parts. In order to verify the feasibility of the platform,to build a large data cloud platform of agricultural machinery parts of the supply chain,to build 8 servers in the Hadoop cluster platform at the bottom,to search various parameters of parts of agricultural machinery for testing purposes,the platform is tested,and the traditional MySQL server are compared. The test results indicate that the search in less data,cloud platforms and traditional server speed,but the search conditions in big data,the data processing speed of cloud platform is the traditional server several times,so as to verify the superiority of cloud platform system,in order to ensure the safety of agricultural machinery parts and traceability technology provides reliable guarantee.
引文
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[2]鲁玉峰,唐婷婷,王橹媛,等.基于BOM航空发动机产品质量追溯管理信息化方法的研究[J].企业管理与信息化,2011(5):31-35.
[3]郑业鲁,刘晓珂,郭洛先,等.基于供应链的蔬菜安全溯源系统的设计与实现[J].广东农业科学,2016(1):145-150.
[4]陈周国,王胜银,付国晴,等.基于Linux QT技术的远程监控GUI设计[J].通讯技术,2009,42(12):234-236.
[5]何剑锋,邬文彪,李宏穆,等.嵌入式Linux系统的Qt/Embedded图形界面开发[J].电子工程师,2007,33(7):46-48.
[6]周名阳,韩秀玲.基于Qt的图像数据网络传输应用研究[J].计算机工程与设计,2011,32(6):1901-1905.
[7]毛明毅,蒋元恒,陈志成.智能家居远程Web管理控制平台的设计与实现[J].微电子学与计算机,2013,30(5):121-124.
[8]张玉萍,邹澎.基于Qt/Embedded视频采集方案的设计与实现[J].电视技术,2012,36(23):65-68.
[9]杨锋,吴华瑞,朱华吉,等.基于Hadoop的海量农业数据资源管理平台[J].计算机工程,2011,37(12):243-244.
[10]刘军霞,王磊,周喜.面向海量数据的电子政务云平台研究[J].计算机与现代化,2013(7):165-165.
[11]周皓东,黄燕,刘炜.基于Wi Fi无线传感器网络的水质监测系统设计[J].传感器与微系统,2015,34(5):99-101.
[12]武琼,陈敏.基于视联网的远程门诊系统应用探讨[J].中国医院管理,2015(4):50-53.
[13]宋凯.嵌入式远程医疗会诊系统的设计[J].计算机测量与控制,2014(12):2860-2861.
[14]刘振,李念强.远程家庭医疗保健系统[J].工业控制计算机,2015(1):26-27.
[15]尤若宁,周文光.便携式医用设备关键技术的研究[C]//中华医学会全国学术年会,2015.
[16]丁有源,汪安民.基于多核任务并行处理的DSP软硬件设计[J].单片机与嵌入式系统应用,2012,158(8):43-45.
[17]张旭飞,张燕,梁栋.基于PLC的椰子切割机的设计与控制研究[J].农机化研究,2012,34(3):199-202.
[18]顾宝兴,姬长英,王海青,等.智能移动水果采摘机器人设计与试验[J].农业机械学报,2012,43(6):153-160.
[19]李文凤,彭智勇,李德毅,等.不确定性Top-k查询处理[J],软件学报,2012,23(6):1542-1560.
[20]张晓辉,李莹,王华勇,等.应用特征聚合进行中文文本分类的改进KNN算法[J].东北大学学报,2003,24(3):229-233.
[21]王海青,姬长英,顾宝兴,等.基于机器视觉和支持向量机的温室黄瓜识别[J].农业机械学报,2012,43(3):163-167.
[22]王辉,毛文华,刘刚,等.基于视觉组合的苹果作业机器人识别与定位[J].农业机械学报,2012,43(12):165-170.
[23]魏泽鼎,贾俊国,王占永.基于视觉传感器的棉花果实定位方法[J].农机化研究,2012,34(6):66-68,112.
[24]高春城.我国农业发展的资源环境问题与展望[J].当代生态农业,2013,3(4):151-154.
[25]万宝瑞.当前我国农业发展的趋势与建议[J].农业经济问题,2014,4(1):110-114.
[26]徐茂,邓蓉.国内外设施农业发展比较[J].北京农学院学报,2014,29(2):75-79.
[27]陈实,武杰.一种基于以太网的嵌入式数据传输速率优化方法研究[J].微型机与应用,2015(4):64-66.
[28]周芬.基于物联网架构的纺织品仓库温湿度监控系统设计[J].物流技术,2014(17):453-455.
[29]辛海亮,钟佩思,朱绍琦,等.基于Zig Bee的物联网智能家居控制系统[J].电子技术应用,2013,39(12):79-85.