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This paper presents a remote vibration monitoring system for combustion engines, utilising edge computing technology. The proposed solution aims to enhance real-time data processing and reduce latency by performing computations closer to the data source. The system integrates vibration sensor, edge computing units, and potentially cloud-based analytics to provide continuous monitoring and early fault detection. The research discusses the architecture, data acquisition process, and implementation challenges. The experimental results show that analysing the values of specific vibration signal measures can be effective in identifying engine anomalies. The results suggest that edge processing can significantly contribute to the reliability of vibration monitoring in similar applications.
