In this article, we propose malfunction classifications for trucks, a novel idea for smart fleet
management systems. In the proposed cooperative cooperative intelligent transportation (C …

This paper presents a description of a real-world, multivariate time series dataset collected
from an anonymized engine component (called Component X) of a fleet of trucks from …

This study develops a novel semi-supervised approach for detecting Air Pressure System
(APS) failures in Heavy-Duty Vehicles (HDVs) by exploiting two modern Machine Learning …

In recent years, the latest maintenance modelling techniques that adopt the data-based
method, such as machine learning (ML), have brought about a broad range of useful …

The rapid influx of data-driven models into the industrial sector has been facilitated by the
proliferation of sensor technology, enabling the collection of vast quantities of data …

A problem with machine learning (ML) techniques for detecting intrusions in the Internet of
Things (IoT) is that they are ineffective in the detection of low-frequency intrusions. In …

Air pressure systems play an essential role in Scania trucks, so that the correct operation of
the braking system and gear shifting system of Scania cars depends on the health of the air …

The air pressure system (APS) is an integral component of Scania trucks and other heavy
machinery. Because the brakes on these vehicles use air pressure, keeping the APS in …

The reliability of Heavy-Duty Vehicles (HDVs) is critical for continuous operations in sectors
like transportation and logistics. However, the complexity of these vehicles' subsystems …

This paper addresses the prediction of failures in the air pressure system of Scania trucks to
minimize associated operating costs. A custom ensemble model is proposed combining …