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Joint Subjective and Objective Data Capture and Analytics for Automotive Applications

Mathias Johanson ; Jonas Jalminger ; Emmanuel Frécon ; Boel Nelson (Institutionen för data- och informationsteknik, Nätverk och system (Chalmers) ) ; Tomas Olovsson (Institutionen för data- och informationsteknik, Nätverk och system (Chalmers) ) ; Mats Gjertz
Proceedings of the 2nd IEEE International Workshop on Vehicular Information Services for the Internet of Things (VISIT 17) (2017)
[Konferensbidrag, refereegranskat]

In this paper we describe a novel technological framework for capture and analysis of both objective measurement data and subjective user experience data for automotive applications. We also investigate how the framework can be extended to address privacy issues by enforcing a rigorous privacy model called differential privacy. The system under development integrates a telematics system with a smartphone app service architecture and a data-driven analytics framework. The hypothesis is that the framework will improve the opportunities of conducting large scale user trials of automotive functions and services, while improving the quality of collected data. To achieve this, a number of challenges are addressed in the paper, including how to design the subjective data capture mechanisms to be both simple to use yet powerful, how to correlate subjective data with objective measurement data, and how to protect the privacy of users.

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Denna post skapades 2017-09-25. Senast ändrad 2017-10-20.
CPL Pubid: 252059


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