The Processing Architecture based on Measurement Metadata (PAbMM) is a data stream management system specialized in measurement and evaluation (M&E) projects, which incorporates predictive and detective behavior on data streams. It uses a case based organizational memory for recommending courses of action in each detected online situation and previously modeled by the project definition. In this work the storm topology associated with the online processing in PAbMM is described. Additionally, a new synopses strategy for monitoring entities under analysis is presented and a new schema for training the online classifiers is introduced. This new schema allows indicating to the classifiers the problem characterization, the proposal solution and the associated indicator value (target class). A practical case associated with the weather radar of the Experimental Agricultural Station (EAS) INTA Anguil (Province of La Pampa, Argentina) is shown, indicating the advantages of this storm topology and the new schema oriented to training data set.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)