A New Approach Based on ELK Stack for the Analysis and Visualisation of Geo-referenced Sensor Data

Autor: Thi Thu Trang Ngo, David Sarramia, Myoung-Ah Kang, François Pinet
Přispěvatelé: Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Laboratoire de Physique de Clermont (LPC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: SN Computer Science
SN Computer Science, 2023, 4 (3), pp.241. ⟨10.1007/s42979-022-01628-6⟩
ISSN: 2662-995X
2661-8907
DOI: 10.1007/s42979-022-01628-6⟩
Popis: International audience; This paper examines the use of Elasticsearch for data warehousing and analyses of geo-referenced sensor data. Elasticsearch has several advantages compared to its direct competitors. For example, it is capable of handling time series, spatial data, and objects. Moreover, it is natively connected with the data shippers Beats, Logstash, and the visualisation tool Kibana. This paper proposes a method to implement and query multidimensional models in Elasticsearch. No prior work has evaluated Elasticsearch for data warehouses and analytical queries, especially for sensor environmental data. This paper therefore also presents extensive experiments to evaluate its querying performance. The proposed approach is applied to the analysis of sensor data used in the context of CEBA, an environmental cloud solution developed to collect, store, and analyse environmental data. An experimental performance analysis is also provided.
Databáze: OpenAIRE
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