Big Data Analytics for Smart Cities
Big Data Analytics for Smart Cities
复制标题
DOI：
10.1007/978-3-319-60435-0_15
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
V. Bassoo;V. Ramnarain-Seetohul;V. Hurbungs;T. P. Fowdur;Y. Beeharry
中科院分区：
文献类型：
--
作者：
V. Bassoo;V. Ramnarain-Seetohul;V. Hurbungs;T. P. Fowdur;Y. Beeharry
智慧城市的主要目标是改善公民的福祉，促进经济发展，同时保持可持续性。智慧城市可以增强医疗、教育、交通和农业等多种服务。智慧城市基于ICT框架，包括物联网（IoT）技术。这些技术创建了大量的异构数据，通常称为大数据。然而，这些数据本身是没有意义的。需要开发新的流程来解释收集的大量数据，一个解决方案是应用大数据分析技术。大数据可以通过分析技术进行挖掘和建模，以获得更好的洞察力并增强智慧城市功能。在本章中，介绍了四种最先进的大数据分析技术。讨论了大数据分析在智慧城市五个领域的应用，最后概述了智慧城市大数据和分析的安全挑战。
The main objectives of smart cities are to improve the well being of its citizens and promote economic development while maintaining sustainability. Smart cities can enhance several services including healthcare, education, transportation and agriculture among others. Smart cities are based on the ICT framework including the Internet of Things (IoT) technology. These technologies create voluminous amount of heterogeneous data, which is commonly referred to as big data. However these data are meaningless on their own. New processes need to be developed to interpret the huge amount of data gathered and one solution is the application of big data analytics techniques. Big data can be mined and modelled through the analytics techniques to get better insight and to enhance smart cities functionalities. In this chapter, four state-of-the-art big data analytics techniques are presented. Applications of big data analytics to five sectors of smart cities are discussed and finally an overview of the security challenges for big data and analytics for smart cities is elaborated.