%0 Journal Article
	%A Antonis Sideris and  Elias Chlis Kalogeropoulos and  Konstantia Moirogiorgou
	%D 2021
	%J International Journal of Mechanical and Mechatronics Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 175, 2021
	%T Data Analysis Techniques for Predictive Maintenance on Fleet of Heavy-Duty Vehicles
	%U https://publications.waset.org/pdf/10012125
	%V 175
	%X The present study proposes a methodology for the efficient daily management of fleet vehicles and construction machinery. The application covers the area of remote monitoring of heavy-duty vehicles operation parameters, where specific sensor data are stored and examined in order to provide information about the vehicle’s health. The vehicle diagnostics allow the user to inspect whether maintenance tasks need to be performed before a fault occurs. A properly designed machine learning model is proposed for the detection of two different types of faults through classification. Cross validation is used and the accuracy of the trained model is checked with the confusion matrix.
	%P 300 - 304