Abstract
System states of facilities can be recorded and evaluated automatically using sensors, allowing predictive maintenance. In our project, a platform was developed that collects, stores, processes, and displays sensor data from facilities in real time. With machine learning models, derived features are used to make predictions and classifications to determine, for example, the ideal time for an oil change. Training and use of the models in real-time processes as well as forecasting are integrated into the platform, a dashboard visualizes the results. Small and medium enterprises in particular can use AI-based services via the platform without having to set up their own IT infrastructure.
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