Vehicle Maneuver Detection with Accelerometer-Based Classification
by
Javier Cervantes-Villanueva †, Daniel Carrillo-Zapata †, Fernando Terroso-Saenz *,†
, Mercedes Valdes-Vela and Antonio F. Skarmeta
Javier Cervantes-Villanueva †, Daniel Carrillo-Zapata †, Fernando Terroso-Saenz *,†, Mercedes Valdes-Vela and Antonio F. Skarmeta
Department of Communications and Information Engineering, Computer Science Faculty, University of Murcia, 30080 Murcia, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Sensors 2016, 16(10), 1618; https://doi.org/10.3390/s16101618
Received: 12 July 2016 / Revised: 14 September 2016 / Accepted: 23 September 2016 / Published: 29 September 2016
(This article belongs to the Section Physical Sensors)
In the mobile computing era, smartphones have become instrumental tools to develop innovative mobile context-aware systems. In that sense, their usage in the vehicular domain eases the development of novel and personal transportation solutions. In this frame, the present work introduces an innovative mechanism to perceive the current kinematic state of a vehicle on the basis of the accelerometer data from a smartphone mounted in the vehicle. Unlike previous proposals, the introduced architecture targets the computational limitations of such devices to carry out the detection process following an incremental approach. For its realization, we have evaluated different classification algorithms to act as agents within the architecture. Finally, our approach has been tested with a real-world dataset collected by means of the ad hoc mobile application developed.
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MDPI and ACS Style
Cervantes-Villanueva, J.; Carrillo-Zapata, D.; Terroso-Saenz, F.; Valdes-Vela, M.; Skarmeta, A.F. Vehicle Maneuver Detection with Accelerometer-Based Classification. Sensors 2016, 16, 1618.
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