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Use of Sensor Data Warehouse for Soil Moisture Analysis
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Author(s): Myoung-Ah Kang (Université Blaise Pascal, France), François Pinet (Irstea – Clermont Ferrand, France), Sandro Bimonte (Irstea – Clermont Ferrand, France), Gil De Sousa (Irstea – Clermont Ferrand, France)and Jean-Pierre Chanet (Irstea – Clermont Ferrand, France)
Copyright: 2016
Pages: 15
Source title:
Automated Enterprise Systems for Maximizing Business Performance
Source Author(s)/Editor(s): Petraq Papajorgji (Universiteti Europian i Tiranes, Albania), François Pinet (National Research Institute of Science and Technology for Environment and Agriculture, France), Alaine Margarete Guimarães (State University of Ponta Grossa, Brazil)and Jason Papathanasiou (University of Macedonia, Greece)
DOI: 10.4018/978-1-4666-8841-4.ch003
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Abstract
More and more data are collected via sensors. Wireless networks can be implemented to facilitate the collection of sensors data and to reduce the cost of their acquisition. In this chapter, we present a general architecture combining Wireless Sensor Network (WSN) and Spatial Data Warehouse (SDW) technologies. This innovative solution is used to collect automatically sensor's information and to facilitate the analysis of these data. The WSN used in this application has been deployed by Irstea and tested during several years in vineyards in South of France. The novel contribution presented in this chapter is related to the use of a SDW to manage data produced by geo-referenced sensor nodes. SDW is one of the most appropriate modern technologies for analyzing large data sets at different temporal and spatial scales. This type of databases is a specific category of information system used to integrate, accumulate and analyze information from various sources. These data are usually organized according to a multidimensional schema to facilitate the calculation of indicators. In this chapter, we introduce the development of a SDW storing the data collected by this WSN. The implemented data warehouse can allow users to aggregate and explore interactively data produced by sensors. With this system, it is possible to visualize on a map the results of these aggregations.
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