This paper proposes a method to rank air-conditioning systems in a building based on drift anomalies in sensor measurements. The proposed method employs an approach to estimate the drift anomalies from changes in the sensor measurement data of the systems. However, the changes depend on the contexts in which the systems work as well as the drift anomalies. Thus, we propose feature selection and drift anomaly estimation that depend on the contexts. Experimental results imply that the proposed method will be benefical even in a case where the drift anomalies arise over the course of a year.
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