Vehicle Maneuver Detection with Accelerometer-Based Classification.
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.
Department of Communications and Information Engineering, Computer Science Faculty, University of Murcia, 30080 Murcia, Spain. javier.cervantes@um.es.
Javier
J
Cervantes-Villanueva
Department of Communications and Information Engineering, Computer Science Faculty, University of Murcia, 30080 Murcia, Spain. daniel.carrillo2@um.es.
Daniel
D
Carrillo-Zapata
Department of Communications and Information Engineering, Computer Science Faculty, University of Murcia, 30080 Murcia, Spain. fterroso@um.es.
Fernando
F
Terroso-Saenz
Department of Communications and Information Engineering, Computer Science Faculty, University of Murcia, 30080 Murcia, Spain. mdvaldes@um.es.
Mercedes
M
Valdes-Vela
Department of Communications and Information Engineering, Computer Science Faculty, University of Murcia, 30080 Murcia, Spain. skarmeta@um.es.
Antonio F
AF
Skarmeta
accelerometer classification; mobile system; vehicle maneuver detection
Inform Health Soc Care. 2013 Jan;38(1):37-53
22657250
Sensors (Basel). 2015 Jan 19;15(1):2059-85
25608213