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Application and Research of the Intelligent Management System Based on Internet of Things Technology in the Era of Big Data

机译:基于大数据时代的事物技术智能管理系统的应用与研究

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With the in-depth application of the Internet of Things, many emerging technologies are changing the global industry landscape on an unprecedented scale. At the same time, they also provide an opportunity for the development of intelligent management to break through the bottleneck. The proposal and evolution of the concept of intelligent management makes the development of management technology more advanced. Therefore, the introduction of the Internet of Things technology into intelligent management has very important research significance and value. First, conduct research on the origin and current situation of the Internet of Things technology at home and abroad and understand the relevant theories and cutting-edge technologies of the Internet of Things technology. Second, take the enterprise as an example to study the process flow and existing problems in the logistics link in the factory, combine the management concept of the Internet of Things, and integrate IC card identification technology, RFID radio frequency identification technology, barriers and ground sensing technology, and OPC/PLC. Third, combined with PLC/OPC technology, the design and integration of the software system and hardware system are realized. The experimental results show that the system modules have been tested to provide company information management, employee multifactor predictive analysis, and efficient batch efficiency evaluation, which has a certain value for company data management and data analysis and mining, and improve company efficiency by more than 30%.
机译:随着物联网的深入应用,许多新兴技术正在以前所未有的规模改变全球产业景观。与此同时,他们还为开发智能管理突破瓶颈提供了机会。智能管理概念的提案和演变使得管理技术的发展更先进。因此,将事物互联网技术引入智能管理具有非常重要的研究意义和价值。首先,对国内外事物技术互联网的起源和现状进行研究,了解物联网技术的相关理论和尖端技术。二,采取企业作为一个例子来研究过程流程和物流链接中的现有问题,结合了物流互联网的管理理念,并集成了IC卡识别技术,RFID射频识别技术,障碍和地面传感技术和OPC / PLC。第三,结合PLC / OPC技术,实现了软件系统和硬件系统的设计和集成。实验结果表明,系统模块已经过测试,提供公司信息管理,员工多因素预测分析和高效的批量评估,这对公司数据管理和数据分析和采矿具有一定的价值,并提高公司效率超过30%。

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