Social data analysis framework in cloud and Mobility Analyzer for Smarter Cities

Linlin You, G. Motta, D. Sacco, Tianyi Ma
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引用次数: 21

Abstract

One emerging and challenging issue in Smarter Cities is Mobility. In order to gather mobility data for relevant analyses, two solutions are widely discussed, namely the conventional standardized infrastructure sensors and the novel social sensing solution. However infrastructure sensors solution is too costly, that is unfeasible for every city. On the contrast, social sensing is a renewal approach, by which people perform “sensory data” collection tasks. In order to widely conduct the second solution and meet various needs of cities, it requires the ability to 1) support various social data sources, 2) be scalable, customizable and configurable, and 3) use cost-efficient IT resources. However current research cannot overcome these challenges. Therefore, this paper presents a social sensing data analysis framework in cloud for smarter cities, especially to support smart mobility. As a case study, Mobility Analyzer, a subsystem of IRMA (Integrated Real-time Mobility Assistant, that is a pilot project of Pavia, Italy), is implemented.
云中的社会数据分析框架和智慧城市的移动分析器
智慧城市的一个新兴和具有挑战性的问题是机动性。为了收集移动数据进行相关分析,人们广泛讨论了两种解决方案,即传统的标准化基础设施传感器和新型社会传感解决方案。然而,基础设施传感器解决方案成本过高,并非适用于每个城市。相反,社会感知是一种更新的方法,人们通过它来执行“感官数据”收集任务。为了广泛实施第二种解决方案,满足城市的各种需求,需要具备1)支持各种社会数据源的能力,2)可扩展、可定制和可配置的能力,3)使用具有成本效益的it资源。然而,目前的研究还不能克服这些挑战。为此,本文提出了一种面向智慧城市的云环境下社会传感数据分析框架,以支持智能出行。以意大利帕维亚试点项目IRMA (Integrated Real-time Mobility Assistant)的一个子系统Mobility Analyzer为例进行了研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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