International Business Machines Corporation
SENSOR SIGNAL PREDICTION AT UNREPORTED TIME PERIODS

Abstract:

A method, a computer program product, and a system for predicting low-frequency sensor signal predictions using a hierarchical prediction model. The method includes receiving a historical dataset of high-frequency sensor signal data and low-frequency sensor signal data. The method also includes generating a Gaussian process regression model using the historical dataset and sensor parameters and outputting high-frequency sensor signal predictions. The method also includes generating a hierarchical Gaussian process model using the historical dataset and the high-frequency sensor signal predictions and predicting low-frequency sensor signal predictions.