@misc{10481/99239,
year = {2022},
url = {https://hdl.handle.net/10481/99239},
abstract = {The enormous quantity of data handled by
building management systems are key to develop more
efficient energy operational systems. However, the inability
of current systems to take benefit from the generated data
may waste good opportunities of improving building performance.
Big Data appears as a suitable framework to sustain
the management system and conduct future prospective
analysis. In this article, we present a Big Data-based architecture
for the efficient management of buildings. The
different Big Data components are involved not only in the
data acquisition phase, but also in the implementation of algorithms
capable of analyzing massive data collected from
very heterogeneous sources. They also enable fast computations
that can help the generation of optimal operational
plan generations to improve the building functioning. The
proposed architecture has been effectively introduced in
four different-purpose buildings, demonstrating that Big
Data can help during the energy cycle of the building.},
title = {Big data architecture for building energy management systems},
doi = {https://doi.org/10.1109/TII.2021.3130052},
author = {Ruiz Jiménez, María Dolores and Gómez Romero, Juan and Fernández Basso, Carlos Jesús and Martín Bautista, María José},
}