Presentación de avances en el 2015 International Workshop on Data Mining with Industrial Applications (DMIA 2015)

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Como parte del convenio de vinculación tecnológica entre la Facultad de Ingenieria de la Universidad Nacional de La Pampa y el INTA Anguil el equipo de trabajo presento avances de las lineas de desarrollo en el 2015 International Workshop on Data Mining with Industrial Applications (DMIA 2015).

Abstract

The Weather Radar (WR) of the Experimental Agricultural Station (EAS) INTA Anguil produces daily a volume of 17GB of data, which represents about 6.2 Tb annually. The use of such data when they are generated, as well as its subsequent management, use and the possibility of providing services to the public represent a challenge in terms of volume and complexity. The Strategy for Data Stream Processing based on Measurement Metadata (SDSPbMM) is a data stream manager sustained in a measurement and evaluation framework, which incorporates detective and predictive behavior, through the use of measurements and associated metadata. This paper proposes a processing architecture that extends the SDSPbMM to incorporate the processing of big data. This would provide the WR of a detective and predictive behavior on online data, as well as include a layer of public services, which encourages the consumption of data generated by the WR of INTA Anguil._

El trabajo fue publicado en el IEEE Conference Proceedings.

Como Citar

M. J. Diván, Y. B. Saibene, M. De Los Ángeles Martín, M. L. Belmonte, G. Lafuente and J. Caldera, “ Towards a Data Processing Architecture for the Weather Radar of the INTA Anguil,” 2015 International Workshop on Data Mining with Industrial Applications (DMIA), San Lorenzo, Paraguay, 2015, pp. 72-78, doi: 10.1109/DMIA.2015.12. keywords: {Meteorology;Metadata;Context;Meteorological radar;Monitoring;Computer architecture;Big Data;Remote Sensing;Data Stream Processing;Organizational Memory},