大数据背景下高校智慧校园集成平台的设计与实践

Juanyu Yang, Yang Chen, Xiao-jun Liu, Xiuchao Luo
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引用次数: 0

摘要

高校智能校园建设可以通过数据资源的合理布局,为师生提供更加人性化的服务,更好地促进教育的进步。因此,本文对大数据背景下高校智慧校园集成平台的设计与实践进行了研究。本文采用hadoop分布式存储和spark计算组件,并采用javaweb技术开发该平台。在系统性能方面,平均数据响应时间为53 ms,误码率可达到0.3%以下,平均数据库大小为122.7 tb,查询次数可达到1万次以上。本文对数据共享与交换的过程进行了深入研究,并在此基础上提出了高校智能校园一体化的具体建设方案,总结了校园数据的智能化应用与服务模式。实验表明,本研究有利于提高校园数据治理的准确性,同时提高校园管理服务的协同性,满足智慧校园的长远发展需求。
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Design and Practice of University Smart Campus Integration Platform under the Background of Big Data
The construction of intelligent campus in colleges and universities can provide more humanized services to teachers and students through rational distribution of data resources, which can better promote the progress of education. Therefore, this paper studies the design and practice of the integrated platform of smart campus in colleges and universities under the background of big data. In this paper, hadoop distributed storage and spark computing components are used, and javaweb technology is used to develop this platform. In terms of system performance, the average data response time is 53 m s, the bit error rate can reach below 0.3%, the average database size is 122.7 T B, and the number of queries can reach more than 10 000 times. This paper makes an in-depth study on the process of data sharing and exchange, and on this basis, puts forward a concrete construction scheme for the integration of intelligent campus in colleges and universities, and sums up the intelligent application and service mode of campus data. The experiment shows that this research is conducive to improving the accuracy of campus data governance, at the same time, improving the collaboration of campus management services, and meeting the long-term development needs of intelligent campus.
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