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Review

Cognitive Systems for the Energy Efficiency Industry

by
Javier Arevalo
1,
Juan-Ignacio Latorre-Biel
1,
Francisco-Javier Flor-Montalvo
1,
Mercedes Perez-Parte
2 and
Julio Blanco
2,*
1
Department of Mechanical Engineering, Public University of Navarra, Av de Tarazona s/n, 31500 Tudela, Navarra, Spain
2
Department of Mechanical Engineering, University of La Rioja, 26004 Logroño, La Rioja, Spain
*
Author to whom correspondence should be addressed.
Energies 2024, 17(8), 1860; https://doi.org/10.3390/en17081860
Submission received: 6 March 2024 / Revised: 27 March 2024 / Accepted: 10 April 2024 / Published: 13 April 2024
(This article belongs to the Section K: State-of-the-Art Energy Related Technologies)

Abstract

This review underscores the pivotal role of Cognitive Systems (CS) in enhancing energy efficiency within the industrial sector, exploring the application of sophisticated algorithms, data analytics, and machine learning techniques to the real-time optimization of energy consumption. This methodology has the potential to reduce operational expenses and further diminish environmental repercussions; however, it also leverages data-driven insights and predictive maintenance to foresee equipment malfunctions and modulate energy utilization accordingly. The viability of integrating renewable energy sources is emphasized, supporting a transition towards sustainability. Furthermore, this research includes a bibliometric literature analysis from the past decade on the deployment of CS and Artificial Intelligence in enhancing industrial energy efficiency.
Keywords: cognitive systems; energy efficiency industry; cognitive computing applications; artificial consciousness cognitive systems; energy efficiency industry; cognitive computing applications; artificial consciousness

Share and Cite

MDPI and ACS Style

Arevalo, J.; Latorre-Biel, J.-I.; Flor-Montalvo, F.-J.; Perez-Parte, M.; Blanco, J. Cognitive Systems for the Energy Efficiency Industry. Energies 2024, 17, 1860. https://doi.org/10.3390/en17081860

AMA Style

Arevalo J, Latorre-Biel J-I, Flor-Montalvo F-J, Perez-Parte M, Blanco J. Cognitive Systems for the Energy Efficiency Industry. Energies. 2024; 17(8):1860. https://doi.org/10.3390/en17081860

Chicago/Turabian Style

Arevalo, Javier, Juan-Ignacio Latorre-Biel, Francisco-Javier Flor-Montalvo, Mercedes Perez-Parte, and Julio Blanco. 2024. "Cognitive Systems for the Energy Efficiency Industry" Energies 17, no. 8: 1860. https://doi.org/10.3390/en17081860

APA Style

Arevalo, J., Latorre-Biel, J.-I., Flor-Montalvo, F.-J., Perez-Parte, M., & Blanco, J. (2024). Cognitive Systems for the Energy Efficiency Industry. Energies, 17(8), 1860. https://doi.org/10.3390/en17081860

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