DocumentCode
1791621
Title
Big Automotive Data: Leveraging large volumes of data for knowledge-driven product development
Author
Johanson, Mathias ; Belenki, Stanislav ; Jalminger, Jonas ; Fant, Magnus ; Gjertz, Mats
Author_Institution
Alkit Commun. AB, Mölndal, Sweden
fYear
2014
fDate
27-30 Oct. 2014
Firstpage
736
Lastpage
741
Abstract
To be successful in the increasingly competitive consumer vehicle market, automotive manufacturers must be highly responsive to customer needs and market trends, while responding to the challenges of climate change and sustainable development. One key to achieving this is to promote knowledge-driven product development through large scale collection of data from connected vehicles, to capture customer needs and to gather performance data, diagnostic data and statistics. Since the volume of data collected from fleets of vehicles using telematics services can be very high, it is important to design the systems and frameworks in a way that is highly scalable and efficient. This can be described as a Big Data challenge in an automotive context. In this paper, we explore the opportunities of leveraging Big Automotive Data for knowledge driven product development, and we present a technological framework for capture and online analysis of data from connected vehicles.
Keywords
Big Data; automobile manufacture; automotive electronics; customer services; data analysis; product development; Big Data challenge; automotive manufacturer; big automotive data; consumer vehicle market; customer needs; knowledge-driven product development; market trend; online data analysis; telematics services; Automotive engineering; Big data; Context; Monitoring; Product development; Telematics; Vehicles; analytics; automotive telematics; big data;
fLanguage
English
Publisher
ieee
Conference_Titel
Big Data (Big Data), 2014 IEEE International Conference on
Conference_Location
Washington, DC
Type
conf
DOI
10.1109/BigData.2014.7004298
Filename
7004298
Link To Document