Author:
Dolores M.,Fernandez-Basso Carlos,Gómez-Romero Juan,Martin-Bautista Maria J.
Abstract
AbstractThe 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.
Funder
NextGenerationEU
Junta de Andalucía
European Union
European Union – NextGenerationEU
Publisher
Springer Science and Business Media LLC
Reference58 articles.
1. Ruiz, M. D., Gómez-Romero, J., Fernandez-Basso, C. & Martin-Bautista, M. J. Big data architecture for building energy management systems. IEEE Trans. Ind. Inf. 18(9), 5738–5747. https://doi.org/10.1109/TII.2021.3130052 (2021).
2. Lesser, A. How energy data will impact the smart grid (2013). [Last access: 2023-01-31] http://research.gigaom.com/report/how-energy-data-will-impact-the-smart-grid/.
3. Molina-Solana, M., Ros, M., Ruiz, M. D., Gómez-Romero, J. & Martín-Bautista, M. J. Data science for building energy management: A review. Renew. Sustain. Energy Rev. 70, 598–609 (2017).
4. Zhou, T., Song, Z. & Sundmacher, K. Big data creates new opportunities for materials research: A review on methods and applications of machine learning for materials design. Engineering 5(6), 1017–1026 (2019).
5. Naeem, M. et al. Trends and future perspective challenges in big data (2022).