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Sensor deployments in large buildings allow the administrators to supervise the building infrastructure and identify abnormalities. Nevertheless, the numerous data streams reported by the increasing number of sensors overwhelm the building administrators. We propose a methodology that assists them to identify abnormal devices usages. The proposed method takes advantage of Ensemble Empirical Mode Decomposition...
A typical large building contains thousands of sensors, monitoring the HVAC system, lighting, and other operational sub-systems. With the increased push for operational efficiency, operators are relying more on historical data processing to uncover opportunities for energy-savings. However, they are overwhelmed with the deluge of data and seek more efficient ways to identify potential problems. In...
An anomaly detection procedure is defined and its statistical performance are carefully quantified. It is based on a non Gaussian modeling of the marginal distributions of random projections (sketches) of traffic aggregated jointly at different levels (multiresolution). To evaluate false negative vs. false positive in a controlled, reproducible and documented framework, we apply the detection procedure...
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