This paper introduces a spatio-temporal statistical analysis approach appropriate for monitoring or managing a physical system in which measurements are taken over dense time resolution but at sparse locations. The proposed approach is designed for implementation in an automated and efficient operation with manual intervention required only for scenario analysis. The method is based on a modeling framework for complex predictor-response and spatio-temporal relationships, and issues model-based prediction intervals. To accommodate varying practical situations, the method also includes an automated decision criterion for choosing between parametric and nonparametric spatial covariance models. The approach is illustrated using a data center thermal management problem.