Big data technologies in support of real time capturing and understanding of electric vehicle customers dynamics

Robin G. Qiu, Katie Wang, Shan Li, Jin Dong, Ming Xie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

Energy overconsumption and greenhouse gas emission have been contributing to air pollutions and the global warming for years. The unceasingly increasing number of fossil fuels based vehicles around the world is considered as one of main factors making to the situation worse year by year. Electric vehicles (EV) are promoted as a viable and promising alternative transportation means for customers. However, there is an array of issues hindering EVs from the fast adoption in the global auto market. As these issues bear different priorities that surely vary with marketplaces, it becomes essential for EV makers and governments to capture and understand the dynamics of EV consumers in real time. This paper explores how the emerging big data technologies can be applied to facilitate the process of deciphering the acceptance and behavior of EV customers from marketplace to marketplace. A data-collecting web system is discussed. IBM BigInsights platform technologies, including Hadoop, Streams, SPSS modeler and text analytics, are utilized for looking into the insights of collected data. Examples are provided to show the promising future of big data technologies in the field of customer analytics in today's globalized economy.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS
EditorsLi Wenzheng, Eric Tsui, M. Surendra Prasad Babu
PublisherIEEE Computer Society
Pages263-267
Number of pages5
ISBN (Electronic)9781479932788
DOIs
StatePublished - Oct 21 2014
Event2014 5th IEEE International Conference on Software Engineering and Service Science, ICSESS 2014 - Beijing, China
Duration: Jun 27 2014Jun 29 2014

Publication series

NameProceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS
ISSN (Print)2327-0586
ISSN (Electronic)2327-0594

Other

Other2014 5th IEEE International Conference on Software Engineering and Service Science, ICSESS 2014
CountryChina
CityBeijing
Period6/27/146/29/14

All Science Journal Classification (ASJC) codes

  • Software

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