Güven, ÖzlemSahın, Hasan2026-02-122026-02-1220222687-4415https://doi.org/10.46387/bjesr.1093519https://hdl.handle.net/20.500.12885/6485Predictive maintenance is an approach to prevent failure in a system by estimating the time of failure before a mechanical component fails, so that the maintenance decision can be properly planned. In the public transport industry, whose efficiency is heavily dependent on equipment, anticipating breakdowns is vital. In this study, predictive maintenance work was carried out in order to minimize problems such as malfunctions in public transport vehicles, stopping the voyage, delaying the journey and causing an accident due to unplanned breakdowns. Based on instant vehicle health data obtained from IoT sensors, classification techniques were run in machine learning. For maintenance planning, the probability of vehicles being normal and malfunctioning was examined with fuzzy logic and fuzzy outputs were obtained at maintenance speed. With the predictive maintenance approach applied to the data of the study taken from the vehicles, almost all of the faults in the vehicles could be detected.eninfo:eu-repo/semantics/openAccessMachine LearningInternet of ThingsPredictive MaintenanceMaintenanceSmart Public TransportationArticle10.46387/bjesr.1093519418998513495