为发展中国家交通应用提供更智能的大数据分析

T. Pham, Q. Minh, Hong Linh Truong, H. Dam
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引用次数: 1

摘要

物联网(IoT)实时产生大量数据。利用这些数据需要适当的数据存储、分析和计算技术,以便提取有价值的信息并立即采取行动。在本章中,我们介绍了实时交通应用,这是智能城市背景下典型的物联网大数据应用,但适用于发展中国家不可靠和分散的基础设施。我们分析了一个案例研究,以展示在此类基础设施中实施大物联网数据应用时需要解决的挑战。在此基础上,我们概述了我们的关键设计原则和技术。我们提供了几个例子来特别讨论我们如何实现我们的设计和经验教训。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smarter big data analytics for traffic applications in developing countries
Internet of Things (IoT) generates a huge amount of data in real-time. Utilization of such data requires appropriate data storage, analytics, and computation techniques so that valuable information can be extracted and immediate actions could be taken place. In this chapter, we present real-time traffic applications, typical IoT-enabled big data applications in smart city context, but for unreliable and fragmented infrastructures in developing countries. We analyze a case study to show challenges that we need to address when implementing big IoT data applications in such infrastructures. Based on that we outline our key design principles and techniques. We present several examples to particularly discuss how we achieve our designs and lesson learned.
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