@misc{10481/95413,
year = {2023},
month = {11},
url = {https://hdl.handle.net/10481/95413},
abstract = {The enormous amount of data generated by sensors and other data sources in modern grid
management systems requires new infrastructures, such as IoT (Internet of Things) and Big Data
architectures. This, in combination with Data Mining techniques, allows the management and
processing of all these heterogeneous massive data in order to discover new insights that can
help to reduce the energy consumption of the building. In this paper, we describe a developed
methodology for an Internet of Things (IoT) system based on a robust big data architecture. This
innovative approach, combined with the power of Spark algorithms, has been proven to uncover rules
representing hidden connections and patterns in the data extracted from a building in Bucharest.
These uncovered patterns were essential for improving the building’s energy efficiency.},
organization = {Grant PID2021-123960OB-I00 funded by MCIN/
AEI/10.13039/501100011033},
organization = {ERDF A way of making Europe and by the DESINFOSCAN project, founded
by MCIN/AEI/10.13039/501100011033},
organization = {European Union NextGenerationEU/PRTR (Grant TED2021-
1289402B-C21)},
organization = {Universities through the EU-funded
Margarita Salas programme NextGenerationEU},
organization = {Project IA4TES
(MIA.2021.M04.0008), funded by the European Union—NextGenerationEU},
organization = {European Union (Energy IN TIME Project, No. 608981)},
organization = {Grant PID2021-123960OB-I00 funded by MCIN/AEI/10.13039/501100011033 and by ERDF A way of
making Europe},
organization = {DESINFOSCAN project, founded by MCIN/AEI/10.13039/501100011033},
organization = {Ministry of Universities through the EU-funded margarita salas programme NextGenerationEU},
publisher = {Nature Research},
title = {A big data association rule mining based approach for energy building behaviour analysis in an IoT environment},
doi = {10.1038/s41598-023-47056-1},
author = {Ruiz Jiménez, María Dolores and Fernández Basso, Carlos Jesús and Gómez-Romero, Juan and Martín Bautista, María José},
}