Intelligent services for Big Data science
Intelligent services for Big Data science
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DOI：
10.1016/j.future.2013.07.014
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发表时间：
2014-07-01
影响因子：
7.5
通讯作者：
Xhafa, F.
中科院分区：
文献类型：
--
作者：
Dobre, C.;Xhafa, F.
城市是大数据正在产生真实的影响的领域。城市规划者和管理机构只需要指尖上的正确工具来消费城镇或城市产生的所有数据点，然后能够将其转化为改善人们生活的行动。在这种情况下，大数据绝对是一种对我们这些选择生活在城镇或城市的人的生活质量有直接影响的现象。未来的智慧城市不仅依赖于城市基础设施中的传感器，还依赖于大量的设备，这些设备愿意感知并将其数据集成到技术平台中，用于反思个人和城市大社区的习惯和情况。据预测，到2016年，城市每平方公里的城市化土地每天将产生超过4.1 TB的数据。有效地处理如此大量的数据已经是一个挑战。在本文中，我们介绍了我们的解决方案，旨在支持下一代大数据应用程序。我们首先介绍CAPIM，一个平台，旨在自动化的过程中收集和聚合上下文信息的大规模。它集成了旨在收集上下文数据（位置，用户的配置文件和特征以及环境）的服务。随后，我们提出了一个具体的实现智能交通系统的设计上的CAPIM。该应用程序旨在帮助用户和城市官员更好地了解大城市的交通问题。最后，我们提出了一个解决方案，以处理大规模的上下文数据的有效存储。这些服务的结合为智能智慧城市应用提供了支持，利用上下文信息的优势，主动自主地适应和智能地提供服务和内容。(C)2013爱思唯尔有限公司版权所有。
Cities are areas where Big Data is having a real impact. Town planners and administration bodies just need the right tools at their fingertips to consume all the data points that a town or city generates and then be able to turn that into actions that improve peoples' lives. In this case, Big Data is definitely a phenomenon that has a direct impact on the quality of life for those of us that choose to live in a town or city. Smart Cities of tomorrow will rely not only on sensors within the city infrastructure, but also on a large number of devices that will willingly sense and integrate their data into technological platforms used for introspection into the habits and situations of individuals and city-large communities. Predictions say that cities will generate over 4.1 terabytes per day per square kilometer of urbanized land area by 2016. Handling efficiently such amounts of data is already a challenge. In this paper we present our solutions designed to support next-generation Big Data applications. We first present CAPIM, a platform designed to automate the process of collecting and aggregating context information on a large scale. It integrates services designed to collect context data (location, user's profile and characteristics, as well as the environment). Later on, we present a concrete implementation of an Intelligent Transportation System designed on top of CAPIM. The application is designed to assist users and city officials better understand traffic problems in large cities. Finally, we present a solution to handle efficient storage of context data on a large scale. The combination of these services provides support for intelligent Smart City applications, for actively and autonomously adaptation and smart provision of services and content, using the advantages of contextual information. (C) 2013 Elsevier B.V. All rights reserved.