The document proposes a multilayer hardware/software architecture for managing big data from remote wind farms. The architecture applies cloud computing techniques to process large, distributed, and heterogeneous data sets from wind farms, which are difficult to access locations that require remote sensing management. The innovative contribution is combining different techniques at three layers of the proposed architecture for managing and processing big data from wind farms.

1. MULTILAYER BIG DATA ARCHITECTURE FOR REMOTE
SENSING IN EOLIC PARKS
ABSTRACT
Due to their nature, Eolic parks are situated in zones with difficult access. As a result,
management of Eolic parks using remote sensing techniques is of great importance. In addition,
the huge amount of data managed by Eolic parks, together with their nature (distributed,
heterogeneous, produced, consumed at different times, etc.) makes them ideal to apply big data
techniques. In this paper, we present a multilayer hardware/software architecture that applies
cloud computing techniques for managing big data from Eolic parks. This architecture allows
tackling the processing of large, distributed, and heterogeneous data sets in a remote sensing
context. An innovative contribution of this work is the combination of different techniques at
three different layers of the proposed hardware/software architecture for Eolic park big data
management and processing.