Viadero Monasterio, FernandoGarcía Guzmán, JavierMelendez Useros, MiguelJimenez Salas, ManuelLópez Boada, BeatrizLópez Boada, María Jesús2024-01-172024-01-172024-01-11Viadero-Monasterio, F.; García, J.; Meléndez-Useros, M.; Jiménez-Salas, M.; Boada, B.L.; López Boada, M.J. Simultaneous Estimation of Vehicle Sideslip and Roll Angles Using an Event-Triggered-Based IoT Architecture. Machines 2024, 12, 53 (17p.). https://doi.org/10.3390/machines12010053https://hdl.handle.net/10016/39331In recent years, there has been a significant integration of advanced technology into the automotive industry, aimed primarily at enhancing safety and ride comfort. While a notable proportion of these driver-assist systems focuses on skid prevention, insufficient attention has been paid to addressing other crucial scenarios, such as rollovers. The accurate estimation of slip and roll angles plays a vital role in ensuring vehicle control and safety, making these parameters essential, especially with the rise of modern technologies that incorporate networked communication and distributed computing. Furthermore, there exists a lag in the transmission of information between the various vehicle systems, including sensors, actuators, and controllers. This paper outlines the design of an IoT architecture that accurately estimates the sideslip angle and roll angle of a vehicle, while addressing network transmission delays with a networked control system and an event-triggered communication scheme. Experimental results are presented to validate the performance of the IoT architecture proposed. The event-triggered scheme of the IoT solution is used to decrease data transmission and prevent network overload.17engCopyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland.This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) licenseAtribución-NoComercial-SinDerivadas 3.0 EspañaRoll Angle EstimationSideslip Angle EstimationIotEvent-TriggeringInformáticaIngeniería Mecánicahttps://doi.org/10.3390/machines12010053open access11, 5217Machines12AR/0000034018VoR