Ubiquitous Sensorization for Multimodal Assessment of Driving Patterns

  • Fábio Silva
  • Cesar Analide
  • Celestino Gonçalves
  • João Sarmento
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 291)

Abstract

Sustainability issues and sustainable behaviours are becoming concerns of increasing significance in our society. In the case of transportation systems, it would be important to know the impact of a given driving behaviour over sustainability factors. This paper describes a system that integrates ubiquitous mobile sensors available on devices such as smartphones, intelligent wristbands and smartwatches, in order to determine and classify driving patterns and to assess driving efficiency and driver’s moods. It first identifies the main attributes for contextual information, with relevance to driving analysis. Next, it describes how to obtain that information from ubiquitous mobile sensors, usually carried by drivers. Finally, it addresses the multimodal assessment process which produces the analysis of driving patterns and the classification of driving moods, promoting the identification of either regular or aggressive driving patterns, and the classification of mood types between aggressive and relaxed. Such an approach enables ubiquitous sensing of personal driving patterns across different vehicles, which can be used in sustainability frameworks, driving alerts and recommendation systems.

Keywords

Driving Profile Mobile Sensors Sustainability 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Fábio Silva
    • 1
  • Cesar Analide
    • 1
  • Celestino Gonçalves
    • 1
  • João Sarmento
    • 1
  1. 1.Department of InformaticsUniversity of MinhoBragaPortugal

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