- -

Characterizing the driving style behavior using artificial intelligence techniques

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

Characterizing the driving style behavior using artificial intelligence techniques

Show full item record

Meseguer Anastasio, JE.; Tavares De Araujo Cesariny Calafate, CM.; Cano Escribá, JC.; Manzoni, P. (2013). Characterizing the driving style behavior using artificial intelligence techniques. IEEE. http://hdl.handle.net/10251/67314

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/67314

Files in this item

Item Metadata

Title: Characterizing the driving style behavior using artificial intelligence techniques
Author:
UPV Unit: Universitat Politècnica de València. Instituto de Instrumentación para Imagen Molecular - Institut d'Instrumentació per a Imatge Molecular
Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Issued date:
Abstract:
[EN] The On Board Diagnosis (OBD-II) standard allows accessing the vehicles’ Electronic Control Unit (ECU) easily through a Bluetooth OBD-II connector. This paper presents the DrivingStyles architecture, which adopts ...[+]
Subjects: Driving styles , Android smartphone , OBD-II , Neural Networks , Eco-driving , Wireless Network
Copyrigths: Reserva de todos los derechos
Publisher:
IEEE
Publisher version: http://www.ieeelcn.org/prior/LCN38/lcn38demos.html
Conference name: 38th IEEE Conference on Local Computer Networks (LCN 2013)
Conference place: Sydney, Australia
Conference date: October, 21-24, 2013
Description: © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Thanks:
This work was partially supported by the Ministerio de Ciencia e Innovación, Spain, under Grant TIN2011-27543-C03-01, and by the Universitat Politècnica de València through the ABATIS project (PAID-05-12).
Type: Comunicación en congreso

This item appears in the following Collection(s)

Show full item record