The analysis of sensor data is a major activity in an emergency system; it is aimed at extracting useful information and at executing monitoring and anomaly detection. We focus on automatic data analysis through machine learning techniques, which require creating a model of the data that has to be kept up to date to match the evolving status of the environment. The update of a model improves its quality but introduces computation and communication overhead. In this paper we address the problem of identifying the optimal trade off between a low update rate and high quality of the model, we describe two update strategies and we draw considerations from their application on two sets of sensor data. Copyright © 2009 ACM.
Toscani, D., Frigerio, M., Bernini, D. (2009). Dynamic update of data analysis models in emergency systems. In 5th International Wireless Communications and Mobile Computing Conference. ACM [10.1145/1582379.1582389].
Dynamic update of data analysis models in emergency systems
BERNINI, DIEGO
2009
Abstract
The analysis of sensor data is a major activity in an emergency system; it is aimed at extracting useful information and at executing monitoring and anomaly detection. We focus on automatic data analysis through machine learning techniques, which require creating a model of the data that has to be kept up to date to match the evolving status of the environment. The update of a model improves its quality but introduces computation and communication overhead. In this paper we address the problem of identifying the optimal trade off between a low update rate and high quality of the model, we describe two update strategies and we draw considerations from their application on two sets of sensor data. Copyright © 2009 ACM.
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