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Intelligent Maintenance System for Legacy Vehicles

ACIOLI E SILVA, WALMIR; JUNIOR ABULARACH ARNEZ, JUSSIF; LIMA DAMASCENO, MARIA GABRIELA; LANDAU PAIVA DE MEDEIROS, RENAN; DE BESSA, IURY VALENTE; Ferreira de Lucena Junior, Vicente

2025 • 2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA) • 9 citações

Resumo

Predictive maintenance is an approach based on technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), and robust system architectures. It is widely used in industry and is increasingly adopted in the automotive sector, where its application is often limited to newer vehicles and trucks, excluding most older models. To fill this gap, we propose a solution for cars manufactured from 2010 onward with On-Board Diagnostics II (OBD-II). Our system has a low-cost onboard device, the Legacy Internet of Vehicles (IoV), which enables these vehicles to connect to the cloud server. The system’s initial goal is to send telemetry data to the cloud for analysis, identify anomalies, and predict potential future failures. The system alerts users through internet-connected devices when problems are detected, ensuring that notifications are sent directly to the user. By directing processing to the cloud, the system minimizes the complexity required onboard the vehicle, making it an accessible and scalable approach for a wider audience. To validate our solution, we conducted one of the application scenarios for this system. In this first stage, we performed tests with the system, identifying engine temperature alert problems that would immediately notify the user on the registered device, which in this case was the smartphone.

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