In-vehicle electronic equipment aims to increase safety, by detecting risk factors and taking/suggesting corrective actions. This paper presents a knowledge-based framework for assisting a driver via her PDA. Car data extracted under On Board Diagnostics (OBD-II) protocol, data acquired from PDA embedded micro-devices and information retrieved from the Web are properly combined: a simple data fusion algorithm has been devised to collect and semantically annotate relevant safety events. Finally, a logic-based matchmaking allows to infer potential risk factors, enabling the system to issue accurate and timely warnings. The proposed approach has been implemented in a prototypical application for the Apple iPhone platform, in order to provide experimental evaluation in real-world test drives for corroborating the approach.
A Mobile Knowledge-Based System for On-Board Diagnostics and Car Driving Assistance / Ruta, Michele; Scioscia, Floriano; Gramegna, Filippo; DI SCIASCIO, Eugenio. - (2010), pp. 91-96. (Intervento presentato al convegno The Fourth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies tenutosi a Firenze, Italy nel October 25-30, 2010).
A Mobile Knowledge-Based System for On-Board Diagnostics and Car Driving Assistance
RUTA, Michele;SCIOSCIA, Floriano;GRAMEGNA, Filippo;DI SCIASCIO, Eugenio
2010-01-01
Abstract
In-vehicle electronic equipment aims to increase safety, by detecting risk factors and taking/suggesting corrective actions. This paper presents a knowledge-based framework for assisting a driver via her PDA. Car data extracted under On Board Diagnostics (OBD-II) protocol, data acquired from PDA embedded micro-devices and information retrieved from the Web are properly combined: a simple data fusion algorithm has been devised to collect and semantically annotate relevant safety events. Finally, a logic-based matchmaking allows to infer potential risk factors, enabling the system to issue accurate and timely warnings. The proposed approach has been implemented in a prototypical application for the Apple iPhone platform, in order to provide experimental evaluation in real-world test drives for corroborating the approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
